basic life research scientist (1 year fixed term) Jobs in California

basic life research scientist (1 year fixed term)

basic life research scientist (3 year fixed term) Jobs in California

basic life research scientist (3 year fixed term)

bioinformatics engineer ii (18 month fixed-term) (hybrid opportunity) Jobs in California

bioinformatics engineer ii (18 month fixed-term) (hybrid opportunity)

data analyst 1 (1 year fixed term) Jobs in California

data analyst 1 (1 year fixed term)

engineer associate (2 year fixed-term) Jobs in California

engineer associate (2 year fixed-term)

machine learning systems engineer 1 year fixed term

Stanford University

The Department of Ophthalmology in the School of Medicine at Stanford University is launching an interdisciplinary Neuro-AI project dedicated to building a foundation model of the brain. This endeavor will involve multiple labs and faculty across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Leveraging cutting-edge advances in electrophysiology and machine learning, this project aims to create a functional "digital twin" - a model that captures both the activity dynamics of the brain at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking talented systems engineers with extensive experience in large scale data and compute clusters. As a Systems Engineer, you will be responsible for designing, deploying, and maintaining the compute infrastructure that supports our machine learning and data pipeline operations. This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias ( ), Tirin Moore ( ) and other labs at Stanford University renowned for their expertise in perception, cognition, pioneering neural recording techniques, computational neuroscience, machine learning, and Neuro-AI research. Duties include: <ul><li> Design and develop complex and specialized equipment, instruments, or systems; coordinate detailed phases of work related to responsibility for part of a major project or for an entire project of moderate scope. </li><li> Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge. </li><li> Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field. </li><li> Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty. </li><li> Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers. </li><li> Provide technical direction to other research staff, engineering associates, technicians, and/or students, as needed. </li><li> - Other duties may also be assigned </li></ul> What we offer: <ul><li> Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering. </li><li> Work jointly with a vibrant team of researchers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry. </li><li> Competitive salary and benefits. </li><li> Strong mentoring in career development. </li></ul> Application: In addition to completing the application, please send your CV and one page interest statement to: DESIRED QUALIFICATIONS: <ul><li> 3+ years of experience in designing, managing and running large-scale compute infrastructure in the context of machine learning </li><li> Experience with containerization technologies like Docker and orchestration platforms like Kubernetes or SLURM </li><li> Proficiency in scripting languages such as Python, Bash, or PowerShell </li><li> Strong knowledge of Linux/Unix systems administration </li><li> Ability to work effectively in a collaborative, multidisciplinary environment </li><li> Familiarity with modern distributed big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar </li><li> Familiarity with machine learning frameworks like PyTorch or JAX </li><li> In-depth experience with cloud computing resources </li><li> Thorough knowledge of GPU-based HPCs in the context of machine learning. </li></ul> EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant experience, or combination of education and relevant experience. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): <ul><li> Thorough knowledge of the principles of engineering and related natural sciences. </li><li> Demonstrated project management experience. </li></ul> CERTIFICATIONS & LICENSES: None PHYSICAL REQUIREMENTS : <ul><li> Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds. </li><li> Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully. </li><li> Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds. </li></ul> - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. WORKING CONDITIONS: <ul><li> May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights ?10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather. </li><li> May require travel. </li></ul> The expected pay range for this position is $126,810 to $151,461 annually. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form . Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. <img src="https://www.jobg8.com/Tracking.aspx?snYreeyfh7laxm24a959atA2EXWL5Ej6h" width="0" height="0" />

Machine Learning Systems Engineer (1 Year Fixed Term)

Stanford University is seeking a Big Data Architect 1 for a 1 year fixed term (possibility of renewal) to design and develop applications, test and build automation tools and support the development of Big Data architecture and analytical solutions.About Us: The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data.About the Position: We are seeking an experienced ML Data Engineer to drive the programmatic curation, cleaning, and generation of healthcare data. In this role, you will focus exclusively on developing and maintaining automated, ML-accelerated pipelines that ensure high-quality data ready for machine learning applications. Your work will be pivotal in shaping the integrity of our data and supporting downstream predictive models in a complex healthcare environment. You Will Find This Position a Good Fit If: You are passionate about transforming raw healthcare data into valuable insights. You believe in the critical role of robust data curation in advancing machine learning in healthcare. You thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams. You are excited to work with patient-level data and embrace challenges related to data diversity and complexity. Duties include: Design Big Data systems that are scalable, optimized and fault-tolerant. Work closely with scientific staff, IT professional and project managers to understand their data requirements for existing and future projects involving Big Data. Develop, test, implement, and maintain database management applications. Optimize and tune the system, perform software review and maintenance to ensure that data design elements are reusable, repeatable and robust. Contribute to the development of guidelines, standards, and processes to ensure data quality, integrity and security of systems and data appropriate to risk. Participate in and/or contribute to setting strategy and standards through data architecture and implementation, leveraging Big Data, analytics tools and technologies. Work with IT and data owners to understand the types of data collected in various databases and data warehouses. Research and suggest new toolsets/methods to improve data ingestion, storage, and data access. Key Responsibilities: Data Pipeline Engineering: Design, implement, and maintain robust pipelines for the programmatic cleaning, transformation, and curation of healthcare data. Develop automated processes to curate and validate data, ensuring accuracy and compliance with healthcare standards (e.g. OMOP CDM, FHIR). ML Data Engineering: Leverage core machine learning techniques to generate datasets, clean existing health records, join heterogeneous data sources, and enhance data quality for model training. Implement innovative solutions to detect and correct data inconsistencies and anomalies in large-scale healthcare datasets. Healthcare Data Expertise: Work extensively with patient-level health data, ensuring that data handling practices adhere to industry regulations and ethical standards. Utilize the OMOP Common Data Model (OMOP CDM) to standardize and harmonize disparate healthcare data sources, enhancing interoperability and scalability. Collaboration & Continuous Improvement: Collaborate closely with data scientists, clinical informaticians, and engineers to align data engineering practices with analytical and clinical requirements. Continuously monitor, troubleshoot, and optimize data workflows to support dynamic research and operational needs.The expected pay range for this position is $157,945 to $177,385 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website () provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at . For all other inquiries, please submit a contact form. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission. DESIRED QUALIFICATIONS: 3+ years of experience in software development and data engineering with a strong focus on data cleaning, transformation, and creation. Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy). Hands-on experience in building and maintaining automated data pipelines for large-scale data processing. Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied to data quality and augmentation tasks. Expertise in working with healthcare data, including familiarity with the OMOP Common Data Model (OMOP CDM). Strong experience in a Linux environment and comfort with UNIX command-line tools. Proven ability to work collaboratively in multidisciplinary teams and communicate technical concepts effectively. PREFERRED QUALIFICATIONS: Experience with cloud platforms (e.g., GCP, AWS, or Azure) and distributed computing frameworks. Proficiency with version control systems (e.g., Git) and containerization tools (e.g., Docker). Familiarity with healthcare data standards and regulatory requirements. EDUCATION & EXPERIENCE (REQUIRED):Bachelor's degree in scientific or analytic field and five years of relevant experience, or a combination of education and relevant experience.KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): • Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval). • Experience with relational, NoSQL, or NewSQL database systems and data modeling, structured and unstructured. • Experience in parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch). • Experience in scripting languages and experience in debugging them, experience with high performance/systems languages and techniques. • Knowledge of benchmark software development and programmable fields/systems, ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies. • Ability to use and integrate security controls for web applications, mobile platforms, and backend systems. • Experience deploying reliable data systems and data quality management. • Ability to research, evaluate, architect, and deploy new tools, frameworks, and patterns to build scalable Big Data platforms. • Ability to document use cases, solutions and recommendations. • Demonstrated excellence in written and verbal communication skills.CERTIFICATIONS & LICENSES:NonePHYSICAL REQUIREMENTS :• Frequently sit, grasp lightly, use fine manipulation and perform desk-based computer tasks, lift, carry, push pull objects that weigh to ten pounds. • Occasionally sit, use a telephone or write by hand. • Rarely kneel, crawl, climb, twist, bend, stoop, squat, reach or work above shoulders, sort, file paperwork or parts, operate foot and hand controls. - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.<img src="https://www.jobg8.com/Tracking.aspx?qn2dWMJXE5OUYhjpmgXExjIqwGbtR5Eaq" width="0" height="0" />

ML Data Engineer - Healthcare Data Curation & Cleaning (1 Year Fixed Term)

The Division of Primary Care and Population Health seeks to serve our community through caring, learning, and innovation for the whole person through all stages of live. While engaged in practice and teaching, our faculty are dedicated to establishing new knowledge as the basis for future practice and prevention, and to the greatest extent possible applying that knowledge to improve care for all and reduce health disparities.The research scholar will take a leadership role in Pascal Geldsetzer's research group, which is a "dry lab" focused on quantitative analyses of existing, and often publicly accessible, datasets. The group is currently focused on studying the causal effect of shingles vaccination on cognition ( ). In extensions of this work, the group is also interested in the effect of other vaccinations given in old age on dementia as well as the effect of infections on dementia. Key data sources for our projects are electronic health record data, epidemiological cohort studies, mortality data, and other large health-related administrative datasets. The researcher will be expected to publish in high-impact peer-reviewed journals.We are in particular looking for individuals with in-depth experience in econometric/quasi-experimental approaches for causal effect estimation (e.g., regression discontinuity and difference-in-differences). We are looking for someone to start as soon as possible but there is no specific deadline for the application - we hire on an ongoing basis.The initial appointment will be 1-year fixed term. The fixed-term may be renewed for additional years based on business needs.CORE DUTIES:<ul><li>Carrying out data analyses</li><li>Supervising data analyses led by graduate students and postdoctoral fellows</li><li>Writing manuscripts for publication in scientific journals</li><li>Mentoring and advising junior researchers</li><li>Assisting with, and leading the writing of, grant applications for research funding</li><li>Communicating with research funders, data providers, and project administrative staff</li></ul> EDUCATION & EXPERIENCE: • Doctoral degree with quantitative training or research experience. • Training and experience in quasi-experimental techniques (regression discontinuity, difference-in-differences, interrupted time-series, etc.) • A background in health-related research is a plus but not requiredKNOWLEDGE, SKILLS AND ABILITIES:• Strong coding skills in R, Stata, or other statistical software package. • Strong writing and analytical skills. • Ability to prioritize workload.This role is open to candidates anywhere in the United States. Stanford University has five Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range for this position is $93,000 to $148,000 per annum.Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website () provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.Why Stanford is for YouImagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:<ul><li>Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.</li><li>A caring culture. We provide superb retirement plans, generous time-off, and family care resources.</li><li>A healthier you. Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.</li><li>Discovery and fun. Stroll through historic sculptures, trails, and museums.</li><li>Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more.</li></ul> The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form.Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.<img src="https://www.jobg8.com/Tracking.aspx?ANOyqbAIplhxWA3f2rauRKJogh2PM29mo" width="0" height="0" />

Social Science Research Scholar (1-year Fixed Term)

The Enigma Project (enigmaproject.ai) is a research organization based in the Department of Ophthalmology at Stanford University School of Medicine, dedicated to understanding the computational principles of natural intelligence using the tools of artificial intelligence. Leveraging recent advances in neurotechnology and machine learning, this project aims to create a foundation model of the brain, capturing the relationship between perception, cognition, behavior, and the activity dynamics of the brain. This ambitious initiative promises to offer unprecedented insights into the algorithms of the brain while serving as a key resource for aligning artificial intelligence models with human-like neural representations.As part of this project, we seek exceptional individuals with extensive experience building, using, and fine-tuning large-scale multimodal foundation models. The team will be responsible for training frontier models on large-scale data of neuronal recordings - multimodal models, i.e., digital twins of a primate brain, that can relate unprecedented amounts of sensory input to neuronal correlates of perception, action, cognition, and intelligence. We expect the candidate to have expertise in modern deep learning libraries (preferably PyTorch) and recent developments in multimodal foundation and frontier models. This position promises a vibrant atmosphere at Stanford University in a collaborative community renowned for expertise in computational neuroscience and deep learning. Role & Responsibilities: • Implement and optimize the latest machine learning algorithms/models to train multimodal foundation models on neural data • Develop and maintain scalable, efficient, and reproducible machine-learning pipelines • Conduct large-scale ML experiments, using the latest MLOps platforms • Run large-scale distributed model training on high-performance computing clusters or cloud platforms • Collaborate with machine learning researchers, data scientists, and systems engineers to ensure seamless integration of models and infrastructure • Monitor and optimize model performance, resource utilization, and cost-effectiveness • Stay up-to-date with the latest advancements in machine learning tools, frameworks, and methodologies • - Other duties may also be assignedWhat we offer: • An environment in which to pursue fundamental research questions in AI and neuroscience • A vibrant team of engineers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry. • Access to unique datasets spanning artificial and biological neural networks • State-of-the-art computing infrastructure • Competitive salary and benefits package • Collaborative environment at the intersection of multiple disciplines • Location at Stanford University with access to its world-class research community • Strong mentoring in career development.Application: In addition to applying to the position, please send your CV and one-page interest statement to: DESIRED QUALIFICATIONS:Key qualifications: Master's degree in Computer Science or related field with 2+ years of relevant industry experience, OR Bachelor's degree with 4+ years of relevant industry experience 2+ years of practical experience in implementing and optimizing machine learning algorithms with distributed training using common libraries (e.g. Ray, DeepSpeed, HF Accelerate, FSDP) Strong programming skills in Python, with expertise in machine learning frameworks like TensorFlow or PyTorch Experience with orchestration platforms Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and their machine learning services Familiarity with MLOps platforms (e.g. MLflow, Weights & Biases) Strong understanding of software engineering best practices, including version control, testing, and documentationPreferred qualifications: Familiarity with training, fine tuning, and quantization of LLMs or multimodal models using common techniques and frameworks (LoRA, PEFT, AWQ, GPTQ, or similar) Familiarity with modern big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar Experience with AutoML and Neural Architecture Search (NAS) techniques Contributions to open-source machine learning projects or librariesEDUCATION & EXPERIENCE (REQUIRED):Bachelor's degree and three years of relevant experience, or combination of education and relevant experience.KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): • Thorough knowledge of the principles of engineering and related natural sciences. • Demonstrated project management experience. CERTIFICATIONS & LICENSES:None PHYSICAL REQUIREMENTS :• Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds. • Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully. • Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh >40 pounds. - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.WORKING CONDITIONS:• May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights ?10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather. • May require travel. The expected pay range for this position is $126,810 to $151,461 annually. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form . Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. <img src="https://www.jobg8.com/Tracking.aspx?KD66OVFTKeNfPXQGFK6pr%2f54mlnJj9iiw" width="0" height="0" />

Machine Learning Research Engineer (1 Year Fixed Term)

Stanford University, the Personalized Integrative Medicine Laboratory in the Radiology Department ( ) and the Urologic Cancer Innovation Laboratory ( ) is seeking a creative, highly motivated, Research and Development Scientist and Engineer 1 with an interest in developing platforms that integrate and deploy multimodal machine learning methods in clinical applications. The project is focused on developing a software platform to deploy our existing ultrasound-MRI models for prostate cancer detection in clinical practices. The position requires managing complex multi-modal data sets including clinical assessments, laboratory results, radiological images and pathological findings, to develop a user-friendly software that will encompass existing approaches and allows for easy integration of new models. The successful candidate will join the Department of Radiology at Stanford University and will work with a multi-disciplinary team of clinicians, statisticians, computer scientists, and trainees. This position is available immediately and has a 1-year duration, with possibility of extension based on funding availability and mutual agreement. Duties include : <ul><li> Design and develop specialized software and tools; coordinate detailed phases of work related to responsibility for part of a major project. </li><li> Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge. </li><li> Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field. </li><li> Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty. </li><li> Optional: Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers. </li><li> Provide technical directions to other research staff, engineering associates, technicians, and/or students, as needed. </li></ul> - Other duties may also be assigned. DESIRED QUALIFICATIONS: <ul><li> Candidates should have prior experience in software and platform development and C++/python/docker/UIX programming, and be familiar with toolkits, e.g., ITK, opencv, sklearn. </li><li> Candidate should have prior experience with Designing User Interfaces, including image visualization and connect platforms with docker containers. </li><li> Candidates with experience in radiomics, segmentation, image registration are strongly encouraged to apply. </li><li> Candidates should have demonstrated ability to work independently, attention to details, be dedicated and self-motivated. </li><li> Collaborative team spirit, strong communication skills, positive attitude and adherence to highest ethical principles are necessary to be considered. </li><li> The candidate should have knowledge and experience in machine learning and deep learning, visualization, platform implementation. </li><li> The preferred candidate would also have experience with medical image processing, and traditional signal processing techniques. </li></ul> EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant experience, or combination of education and relevant experience. Preferred candidates will have an M.S. with relevant experience or Ph.D. in Biomedical Engineering, Electrical Engineering, Biomedical Informatics, Computer Science or related fields. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): <ul><li> Thorough knowledge of the principles of engineering and related natural sciences. </li><li> Demonstrated project management experience. </li></ul> PHYSICAL REQUIREMENTS : <ul><li> Frequently grasp lightly/fine manipulation, perform desk-based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds. </li><li> Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully. </li><li> Rarely kneel/crawl, climb (ladders, scaffolds, or other), reach/work above shoulders, use a telephone, writing by hand, sort/file paperwork or parts, operate foot and/or hand controls, lift/carry/push/pull objects that weigh > 40 pounds. </li></ul> - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. WORKING CONDITIONS: <ul><li> May be exposed to high voltage electricity, radiation or electromagnetic fields, lasers, noise > 80dB TWA, Allergens/Biohazards/Chemicals /Asbestos, confined spaces, working at heights of 10 feet, temperature extremes, heavy metals, unusual work hours or routine overtime and/or inclement weather. </li><li> May require travel. </li></ul> WORK STANDARDS: <ul><li> Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations. </li><li> Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned. </li><li> Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, . </li></ul> The expected pay range for this position is $127,211 to $154,222 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form . Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. <img src="https://www.jobg8.com/Tracking.aspx?1%2fwdEqK%2fok1FOvth%2bDDf9bKIlNxjAjKga" width="0" height="0" />

Research and Development Scientist and Engineer (1 Year Fixed-Term)

The Department of Ophthalmology in the School of Medicine at Stanford University is launching an interdisciplinary Neuro-AI project dedicated to building a foundation model of the brain. This endeavor will involve multiple labs and faculty across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Leveraging cutting-edge advances in electrophysiology and machine learning, this project aims to create a functional "digital twin" - a model that captures both the activity dynamics of the brain at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking talented software developers/engineers to support the whole team by developing and scaling the systems that allow our scientists to iterate quickly. In this role, you will play a critical role in ensuring the reproducibility and production-readiness of our codebase, as well as implementing Continuous Integration and Continuous Deployment (CI/CD) processes for all teams involved in the project. Your work will be essential in maintaining the highest standards of software quality, reliability, and efficiency. This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias ( ), Tirin Moore ( ) and other labs at Stanford University renowned for their expertise in perception, cognition, pioneering neural recording techniques, computational neuroscience, machine learning, and Neuro-AI research. Role & Responsibilities: • Develop and maintain reproducible, production-grade software/library for various aspects of the project, including data processing, machine learning, and data/compute infrastructure management • Implement and manage CI/CD pipelines using tools like GitHub Actions, Code Coverage, and unit testing frameworks • Collaborate with data scientists, machine learning engineers, and systems engineers to ensure seamless and timely integration of code and infrastructure • Help establish and enforce coding standards, best practices, and documentation guidelines across the project • Conduct code reviews and provide constructive feedback to maintain code quality and consistency • Optimize code performance, scalability, and reliability • Troubleshoot and debug software issues, and provide timely solutions • Stay up-to-date with the latest trends and best practices in software engineering and CI/CD methodologies Duties include: <ul><li> Assess user needs and requirements. </li><li> Design and develop applications that may involve sophisticated data manipulation. </li><li> Maintain and update existing programs. </li><li> Troubleshoot and solve technical problems. </li><li> Create programs to meet reporting and analysis needs. </li><li> Design and implement user and operations training programs. </li><li> Document changes in software for end users. </li><li> Follow team software development methodology. </li><li> Serve as technical resource with respect to applications. </li><li> - Other duties may also be assigned </li></ul> What we offer: <ul><li> Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering. </li><li> Work jointly with a vibrant team of researchers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry. </li><li> Competitive salary and benefits. </li><li> Strong mentoring in career development. </li></ul> Application: In addition to this application, please send your CV and one page interest statement to: The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory for all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. DESIRED QUALIFICATIONS: <ul><li> 3+ years of experience in developing and maintaining production-grade codebases </li><li> Strong programming skills in Python and system-level languages (e.g. C/C++, Rust) </li><li> In-depth experience with version control systems like Git and collaborative development platforms like GitHub </li><li> Experience setting up and maintaining CI/CD principles through tools such as GitHub Actions and Jenkins </li><li> Strong understanding and experience in test-driven software development with knowledge of different testing methodologies such as unit testing, integration testing, and end-to-end testing </li><li> Excellent problem-solving, communication, and collaboration skills </li><li> Ability to work effectively in a fast-paced, multidisciplinary environment </li><li> Experience with containerization technologies like Docker and orchestration platforms like Kubernetes and Slurm </li><li> Experience with the challenges of scientific software development </li><li> Knowledge of software design patterns and architectures </li><li> Experience contributing to and/or maintaining open-source software projects or libraries </li><li> Familiarity with machine learning frameworks such as TensorFlow or PyTorch </li></ul> EDUCATION & EXPERIENCE (REQUIRED): Bachelor's degree and three years of relevant experience or a combination of education and relevant experience. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): <ul><li> Working knowledge of latest software and design standards. </li><li> Ability to define and solve logical problems for technical applications. </li><li> Knowledge of and ability to select, adapt, and effectively use a variety of programming methods. </li><li> Ability to recognize and recommend needed changes in user and/or operations procedures. </li><li> Basic knowledge of software engineering principles. </li><li> Strong knowledge of at least one programming language. </li></ul> CERTIFICATIONS & LICENSES: None PHYSICAL REQUIREMENTS : <ul><li> Constantly perform desk-based computer tasks. </li><li> Frequently sit, grasp lightly/fine manipulation. </li><li> Occasionally stand/walk, writing by hand. </li><li> Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10 pounds </li></ul> - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. WORKING CONDITIONS: May work extended hours, evenings and weekends. The expected pay range for this position is $107,423 to $133,600 annually. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form . Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. <img src="https://www.jobg8.com/Tracking.aspx?K8u%2f7NQsWgo1Vl%2bL0S4Pn7qrNkk1KSrfs" width="0" height="0" />

Software Developer 1 (1 Year Fixed Term)

Bosch Group

Company Description The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models,Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Big Data Visual Analytics, Explainable AI (XAI), Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AIoT solutions for Bosch products and services in application areas such as automated driving, advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions. Originating from the AI research in Silicon Valley, ourFoundation Model Powered AI Enablersgroup plays a pivotal role in shaping the future of industrial AI experiences for Bosch products and services. By fusing cutting-edge machine learning, data analysis, and interactive visualization technologies, we research and develop scalable and transparent AI & big data analytic solutions (e.g., audio, images, sensor logs) for a range of domains, including Industry 4.0 (I4.0), IoT, autonomous driving, and connected vehicles. Our award-winning team (IEEE VIS best paper & best paper runner-ups) actively collaborates with leading academic and industry groups to advance research ideas and disseminate findings in top AI conferences and journals, such as CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG. Job Description As a Technical Lead specializing in Generative AI for 3D Computer Vision, drive innovation at the intersection of GenAI and spatial perception. Lead research and engineering efforts to develop next-generation AI systems for applications in automated driving, industrial automation, and embodied AI. Key responsibilities include: <ul><li>Lead research and development in generative AI and 3D computer vision to enable embodied intelligence across domains such as ADAS/AD, robotics, and industrial automation.</li><li>Advance 3D perception capabilities by integrating large-scale vision-language-action models, enhancing reasoning, explainability, and open-world understanding.</li><li>Architect and implement scalable solutions, translating cutting-edge research into robust, real-world systems within Bosch's platforms.</li><li>Collaborate cross-functionally with global research and engineering teams to ensure seamless technology transfer and system integration.</li><li>Stay at the forefront of innovation by actively engaging with academic and industry communities through conferences, workshops, and technical events.</li></ul> Contribute to intellectual property through high-impact publications and patent submissions, shaping the future of generative 3D AI technologies. Qualifications Basic Qualifications <ul><li>Ph.D. in Computer Science with >= 3 years industry experience after graduation.</li><li>A minimum of 5 years of R&D experience, or an equivalent graduate research background, primarily in AI technologies including 3D Computer Vision, Automotive Motion, Behavioral Planning, etc.</li><li>A minimum of 3 years of Technical Leadership experiences</li><li>Proficiency in one or more programming languages commonly used in machine learning (e.g., Python, C++, Rust) and major machine learning frameworks like PyTorch</li><li>Hands-on experience in computer vision and deep learning, with a strong focus on at least two of the following areas: multimodal transformers or VLMs, multimodal language models, diffusion models, NeRF or gaussian splatting, VLA modeling, 3D scene understanding, sensor calibration, autonomous driving, SfM, behavior modeling / prediction, voxel/BEV grid-based feature representation.</li><li>Strong interpersonal, communication, and teamwork capabilities.</li></ul> Preferred Qualifications <ul><li>Publication record in top venues including CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG.</li><li>Industry experience with building E2E systems and world models for ADAS development.</li><li>Experience in working with hardware systems including sensors such as cameras, depth sensors, IMU, LIDAR, etc.</li><li>Strong background in math and statistics.</li><li>Able to work independently, has strong research and problem-solving skills.</li><li>Good communication and teamwork skills.</li></ul> Additional Information Your well-being matters at Bosch! We offer a competitive compensation and a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. We're investing in your success! Equal Opportunity Employer, including disability / veterans Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. The U.S. base salary range for this full-time position is $180,000 - $ 210,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your Recruiter can share more details about the specific salary range for this position during the interview process. <img src="https://www.jobg8.com/Tracking.aspx?TyfogLXvGD0rK8ESx6zi5GY%2fuP%2bBwWD%2fv" width="0" height="0" />

Technical Lead - GenAI for 3D Computer Vision

Explore 200+ Machine learning systems engineer 1 year fixed term in California this October. Find roles across top companies and apply now to boost your career.