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computational scientist 3 cell tissue genomics

Genentech

<div><div><div>THE POSITION</div><p>
We advance science so that we all have more time with the people we love.</p><p></p><p>
The Department of Cell and Tissue Genomics (CTG) is focused on developing and applying state of the art genomics technologies (e.g. single cell omics, high-content imaging, perturbations, etc) to solve key challenges in disease biology, target discovery, and translational medicine. We are seeking a highly talented, creative, and motivated computational biologist to analyze cutting-edge high-dimensional profiling and screening data, with a particular focus on high-content imaging, to decipher complex cellular circuits. The candidate will collaborate closely with members of the department to extract biological insights from diverse high dimensional data sets and support the development of new technologies, leveraging existing computational workflows and developing novel ones.</p><p></p><p><b>
The Opportunity:</b></p><p></p><p><b>
As an integral member of our dynamic team, you will be:</b></p><p></p><ul><li><p>
Analyzing high-content imaging data from novel technologies including optical pooled screens, spatial transcriptomics, and high-content perturbation screens, with the goal of extracting mechanistic insights into gene function and cellular phenotypes.</p></li><li><p>
Developing methods to analyze and interpret new types of perturbation data.</p></li><li><p>
Applying statistics and machine learning to investigate data and extract biological insights.</p></li><li><p>
Collaborating across diverse, cross-functional teams including experimentalists in CTG and the therapeutic areas and colleagues in the Computational Sciences Center of Excellence and the AI Biology &amp; Translation departments</p></li></ul><p></p><p><b>
Who You Are:</b></p><p></p><ul><li><p>
PhD in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field. Alternatively, a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area. Postdoctoral training is a plus.</p></li><li><p>
Strong publication record of biological discovery and/or methods development.</p></li><li><p>
Deep expertise in image analysis, including image processing, feature extraction, and morphological profiling. Familiarity with modern deep learning approaches (e.g., embeddings, foundation models) is a plus.</p></li><li><p>
Comfortable with the statistical principles behind current best practices in high-throughput data analysis.</p></li><li><p>
Fluent in Python and/or R.</p></li><li><p>
Excellent communication and presentation skills.</p></li><li><p>
Able to work successfully in cross-functional teams to collaboratively solve complex problems.</p></li><li><p>
Passionate about applying your analytical skills to understand health and disease.</p></li></ul><p></p><p><b>
Preferred Experience:</b></p><p></p><ul><li><p>
Experience with in situ data (FISH or ISS barcode calling).</p></li><li><p>
Familiarity with image analysis frameworks or libraries (e.g., CellProfiler).</p></li><li><p>
Experience with genomic data including single cell RNA-seq and perturbation screens is a plus.</p></li><li><p>
Experience with applying machine learning to high throughput datasets is a plus.</p></li></ul><p></p><p>
Relocation benefits are available for this posting.</p><p></p><p>
The expected salary range for this position based on the primary location of California for Senior Scientist is $124,300- $230,900 and Principal Scientist is $143,200-$265,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.</p><p></p><p>
Benefits</p><p></p><p>
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.</p><p></p><p>
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</p></div><p></p>
<div><div>JOB FACTS
</div><div><div><ul><div><b>Job Sub Category</b><b>
</b><p>Research Informatics
</p></div><div><b>Schedule</b><b>
</b><p>Full time
</p></div><div><b>Job Type</b><b>
</b><p>Regular
</p></div><div><b>Posted Date</b><b>
</b><p>Apr 10th 2026
</p></div><div><b>Job ID</b><b>
</b><p>202604-108731</p></div></ul></div></div></div></div><p></p>

Computational Scientist 3 - Cell & Tissue Genomics

Eli Lilly

<div><p>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.</p><p></p><h1 class="jobSectionHeader"><b>
The Opportunity</b></h1><p></p><p>
We are building something unprecedented &mdash; an AI foundation that will push the frontier on what is possible today across drug discovery research, from target identification and disease biology through translational science.</p><p>
The Applied Intelligence for Discovery (AI4D) team is a newly formed group within Lilly Research Laboratories that operates at the intersection of scientific delivery and core platform development. AI4D&rsquo;s mission is connecting scientists to petabyte-scale data through natural language interfaces, automated analysis workflows, and intelligent search &mdash; and to convert early deployments into repeatable system standards and evaluation practices that scale across therapeutic areas.</p><p></p><p>
As a Scientific Data Engineer, you will close that gap. You will build the semantic layer, data harmonization infrastructure, AI-ready data products, and lakehouse architecture that bridge how data is stored and how AI systems need to consume it. You will be working at the intersection of the data infrastructure team and the generative AI engineers who build the systems scientists interact with.</p><h1 class="jobSectionHeader"><b>
Responsibilities</b></h1><p></p><h2 class="jobSectionHeader"><b>
Data Harmonization and Lakehouse Architecture</b></h2><ul><li>
Design and build the data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers</li><li>
Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI system consumption</li><li>
Implement data quality monitoring, automated profiling, and validation checks across harmonization layers</li><li>
Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment</li><li>
Partner with the teams to extend harmonization patterns as data modalities expand beyond genomics and proteomics into spatial transcriptomics, perturbational data (Perturb-Seq), single-cell, and digital pathology</li></ul><h2 class="jobSectionHeader"><b>
Semantic Layer and Schema Engineering</b></h2><ul><li>
Design and maintain a semantic layer over Lilly&rsquo;s multi-omics databases that enables AI systems</li><li>
Create comprehensive schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraints (e.g., statistical thresholds, unit conventions, experimental design metadata)</li><li>
Develop gold-standard question/SQL pairs for each major database, in collaboration with computational biologists and Generative AI Engineers, to serve as training data, few-shot examples, and evaluation benchmarks</li><li>
Build and maintain a data dictionary and ontology mapping layer that translates how scientists think and speak about data (gene names, pathway terms, assay types) into how the data is physically stored</li></ul><h2 class="jobSectionHeader"><b>
AI-Ready Data Products</b></h2><ul><li>
Build and manage vector embedding pipelines for scientific documents, study metadata, and structured data descriptions to power RAG-based retrieval</li><li>
Build integration pipelines that connect heterogeneous data sources &mdash; omics databases, internal publications, electronic lab notebooks, assay results, and clinical annotations &mdash; into a unified, queryable layer</li><li>
Develop and enforce metadata standards that ensure new data sources are AI-accessible from the point of ingestion, not retroactively</li><li>
Design data products that serve multiple consumption patterns: direct SQL access for computational biologists, structured feeds for ML training pipelines, and semantic interfaces for LLM-powered tools</li></ul><h1 class="jobSectionHeader"><b>
Qualifications</b></h1><ul><li>
Bachelors degree in Computer Science, Data Engineering, Bioinformatics, or a related field + 8 years data engineering experience OR Masters degree and 5 years data engineering experience</li><li>
Demonstrated expertise in building data pipelines, ETL/ELT workflows, and data products that serve downstream AI/ML systems</li></ul><h1 class="jobSectionHeader"><b>
Additional Skills/Preferences</b></h1><ul><li>
Phd in data or related field</li><li>
Strong SQL skills and experience with complex relational database schemas (hundreds of tables, multi-level joins, domain-specific conventions)</li><li>
Experience with modern data platform technologies, including at least one of: Databricks, Snowflake, or equivalent lakehouse platforms</li><li>
Experience with modern data engineering tools: dbt, Spark, Airflow, or similar orchestration and transformation frameworks</li><li>
Proficiency in Python for data processing, scripting, and pipeline development</li><li>
Experience with cloud data platforms (AWS preferred: Redshift, Athena, Glue, S3, or similar)</li><li>
Familiarity with at least one of: vector databases, embedding pipelines, or semantic layer tooling</li><li>
Strong communication skills &mdash; you can work effectively with both engineers who think in schemas and scientists who think in biology</li><li>
Experience with biomedical or scientific data: omics datasets (RNA-seq, proteomics, GWAS), clinical data, or laboratory information management systems</li><li>
Experience in pharmaceutical, biotech, or life sciences environments</li></ul><ul><li>
Familiarity with biomedical ontologies and controlled vocabularies (Gene Ontology, MeSH, ChEBI, HGNC) and their application to data integration</li><li>
Experience building data products that serve AI/ML systems &mdash; feature stores, training datasets, evaluation benchmarks, or semantic annotations for text-to-SQL</li><li>
Knowledge of data governance practices in regulated industries: data lineage, access controls, versioning, and auditability</li><li>
Experience with knowledge graph technologies (Neo4j, Amazon Neptune, RDF/SPARQL) or graph-based data modeling</li><li>
Deep experience with Databricks ecosystem: Unity Catalog for data governance, Delta Lake for ACID transactions, MLflow integration, and Databricks SQL for analytics workloads</li><li>
Experience designing data architectures that bridge traditional bioinformatics workflows (Nextflow, R/Bioconductor) with modern lakehouse consumption patterns</li></ul><p></p><p>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.</p><p></p><p>
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.</p><p><br>
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.</p><p></p><p>
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is</p>
$166,500 - $266,200<p></p><p>
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.</p><p></p><p>
#WeAreLilly</p></div>

Advisor - Scientific Data Engineer

Foresite Labs

<div><p>Foresite Labs is a translational R&amp;D team that derives insights from precision measurement and population-scale biology and genetics to address unmet clinical needs. We use human genetics to systematically dissect and understand human disease biology and develop and critically evaluate therapeutic hypotheses. We engage in translational research, transforming basic insights into therapeutic opportunities. Our work supports drug discovery and company formation, and provides the core around which new ideas are realized and incubated. We offer competitive salaries, excellent benefits, a flexible work environment, and the opportunity to learn from top thinkers in various disciplines. Foresite Labs is headquartered in San Francisco and Boston.</p>
<p><b>
What You&rsquo;ll Do</b></p>
<ul>
<li>Build and own production data infrastructure. Design, implement, and operate deterministic data pipelines that feed intelligence layers; ingest clinical, financial, scientific, and commercial data from REST APIs, XML feeds, and file-based sources into clean, queryable analytical layers; own the full lifecycle: pagination, rate limiting, auth, schema drift, idempotency, retries, monitoring, and alerting.</li>
<li>Model and curate high-quality data assets. Perform entity resolution, schema design, and quality enforcement across disparate and heterogeneous data sources; ensure downstream models, agents and dashboards operate on clean and trustworthy data.</li>
<li>Support AI-native workflows. Build vector infrastructure (e.g., embeddings, indexing, retrieval) and structured data interfaces that GenAI agents and LLM orchestrators depend on; ensure AI layers have the right data in the right shape at the right time.</li>
<li>Uphold high engineering standards and collaborate broadly. Lead code and design reviews, establish testing and observability best practices, and mentor peers; partner with ML engineers, computational biologists, and company founders to translate scientific and business goals into maintainable, and scalable technical solutions.</li>
<li>Leverage agentic coding tools (Claude Code, Codex, or similar) to accelerate prototyping, refactoring, and debugging.</li>
</ul>
<p><b>What You&rsquo;ll Bring</b></p>
<ul>
<li>5+ years of professional data engineering experience designing, building, and operating production pipelines end-to-end - including schema design for analytical workloads, entity resolution across messy real-world sources, and data quality enforcement at the pipeline level.</li>
<li>Deep fluency in Python and SQL, writing performant, well-tested data transformation code (dbt or similar), with production experience in pipeline orchestration (e.g., Airflow, Prefect) covering DAG design, scheduling, dependency management, retry/backfill patterns, and alerting.</li>
<li>Hands-on cloud data stack experience across AWS or GCP (e.g., managed Postgres, object storage, query engines, serverless ETL) and working knowledge of IAM, networking, and infrastructure patterns; comfortable with Spark or Trino at scale over Parquet/Iceberg. Terraform, CDK, or Pulumi experience is a plus.</li>
<li>Exposure to vector databases (Pinecone, pgvector, Weaviate, or similar) with an understanding of how embedding-based retrieval fits into LLM-powered applications.</li>
<li>Comfortable building and navigating Unix environments, containers (Docker), and CI/CD pipelines (GitHub Actions or similar).</li>
<li>Mindset for rapid and early‑stage execution: bias for action, ownership of ambiguous problem spaces, and demonstrated ability to prioritize and wear multiple hats.</li>
<li>Strong written and verbal communication skills - comfortable explaining complex ideas clearly to technical and non‑technical partners.</li>
</ul>
<p><b>Nice to Have</b></p>
<ul>
<li>Familiarity with biomedical or life sciences data (e.g., clinical trials, genomics, drug discovery, pharma commercial data).</li>
<li>Familiarity with LLM application patterns: prompting, context engineering, tool use, structured outputs, retrieval-augmented generation (RAG).</li>
<li>Experience with dashboard/BI tooling (Streamlit, Retool, Metabase, or similar).</li>
</ul>
<p><b>Why Foresite Labs</b></p>
<ul>
<li>Impact. Your code will accelerate discovery and bring novel therapeutics closer to patients and will help AI driven scientific innovation.</li>
<li>Autonomy. Small, senior teams give you room to architect and own end‑to‑end solutions without heavy bureaucracy.</li>
<li>Learning. Work at the intersection of software, cloud infrastructure, and biology alongside experts in each domain.</li>
<li>Flexibility &amp; Benefits. Competitive salary and equity, comprehensive healthcare, generous PTO, and hybrid/remote options aligned to our SF or Boston hubs.</li>
<li>Ready to build? Apply today and help us create the software foundation that powers the next generation of companies advancing biotech and scientific innovation.</li>
</ul>
<p>Location: San Francisco, CA</p>
<p>
Salary range: $185,000 - $221,400</p>
<p><i>
Foresite Labs is an equal opportunity employer. We thrive on diversity and collaboration.</i></p></div>

Senior Data Engineer (5+ years)

<div><div><div>THE POSITION</div><p>
A healthier future. It&rsquo;s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That&rsquo;s what makes us Roche.</p><p></p><p>
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche&rsquo;s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&amp;D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new computational sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.</p><p></p><p>
The Computational Sciences Center of Excellence (CS CoE) brings together data, AI, and computational expertise to accelerate innovation across gRED and pRED. Within CS CoE, the Data and Digital Catalyst (DDC) organization leads the modernization of our data ecosystem, enabling scalable, data-driven science.</p><p></p><p>
The Data Capability organization within DDC is responsible for establishing foundational data capabilities, including data connectivity, data compliance, scientific content management and data ingestion, curation, integration, and delivery. The team ensures that high-quality, well-structured datasets are available to power analytics, AI/ML, and scientific discovery across Research and Early Development.</p><div></div><div><b>
THE OPPORTUNITY:</b></div><p>
We are seeking an Associate Data Delivery Specialist to support the delivery and operationalization of real-world data (RWD) and clinical-genomic datasets sourced from external partnerships and public/purchased data collections.</p><p>
In this entry-level role, you will contribute to the coordination, preparation, and delivery of multimodal, high-dimensional datasets, ensuring they are accessible, well-documented, and ready for use in research, analytics, and AI/ML workflows. You will also support interactions with external data providers and internal stakeholders to ensure efficient and compliant data usage.</p><p></p><p>
You will work within a cross-functional environment spanning data engineering, data science, and research teams, helping to enable data-driven discovery across Roche&rsquo;s R&amp;D ecosystem.</p><ul><li><p><i>
RWD Data Operations &amp; Delivery</i><br>
Support intake, tracking, and fulfillment of real-world data requests, including clinical-genomic and multimodal datasets. Assist in preparing datasets for delivery, ensuring completeness, quality, and documentation.</p></li><li><p><i>
External Data Coordination</i><br>
Coordinate with external partners (e.g., Caris, FMI) to support data requests, query submissions, and data returns. Assist in managing communications, timelines, and deliverables.</p></li><li><p><i>
Data Governance &amp; Access Support</i><br>
Assist in managing data access workflows, ensuring appropriate approvals, training, and compliance with data usage agreements. Track data usage and maintain documentation.</p></li><li><p><i>
High-Dimensional Data Handling</i><br>
Work with sequencing, imaging, and proteomics datasets, supporting standardized formatting, validation, and integration readiness. Contribute to handling emerging multimodal data types and evolving standards.</p></li><li><p><i>
Data Delivery &amp; Quality Control</i><br>
Perform quality checks, metadata validation, and documentation to ensure datasets are analysis-ready. Support troubleshooting of data delivery issues and escalate when necessary.</p></li><li><p><i>
AI-Assisted Data Curation Support</i><br>
Contribute to early-stage efforts in AI-enabled data curation and harmonization, supporting improved scalability and efficiency in data delivery workflows.</p></li><li><p><i>
Collaboration Across Teams</i><br>
Partner with internal teams (e.g., AIBT, CBM, gRED TM, pRED DTAs) to support data integration and delivery needs across diverse scientific use cases.</p></li></ul><p></p><p><b>
Who You Are:</b></p><ul><li><p>
PhD and 0-2 years of experience, Master&rsquo;s degree and 3-5 years of experience or a Bachelor&rsquo;s degree and 4-7 years of experience in Data Science, Bioinformatics, Health Informatics, Biomedical Engineering, Computer Science, or a related field and experience working with real-world data, clinical data, or biomedical datasets</p></li><li><p>
Basic understanding of RWD sources (e.g., EHR, claims, registries, clinical-genomic datasets)</p></li><li><p>
Strong attention to detail and commitment to data quality and reliability</p></li><li><p>
Strong organizational and communication skills, with the ability to support multiple stakeholders</p></li><li><p>
You are someone who has the technical skills for: Programming: Python (Pandas) or SQL; familiarity with Bash is a plus. Data Formats: Experience with structured data (CSV, JSON, Parquet); exposure to scientific formats is a plus. Data Platforms: Exposure to cloud environments (AWS S3, GCS, or Azure). Tools: Familiarity with Jupyter notebooks, data portals, or workflow tools is beneficial</p></li></ul><p></p><p><b>
Preferred Qualifications:</b></p><ul><li><p>
Exposure to clinical-genomic or multimodal datasets (e.g., Caris, FMI, or similar)</p></li><li><p>
Familiarity with data governance and compliance in healthcare or life sciences</p></li><li><p>
Exposure to AI/ML workflows or data preparation for analytics</p></li><li><p>
Understanding of FAIR data principles and metadata standards</p></li><li><p>
Interest in working with external data partnerships and large-scale data ecosystems</p></li></ul><p></p><p>
Onsite presence, on our South San Francisco campus, is expected for at least 3 days a week.</p><p></p><p>
Relocation benefits are not available for this job posting.</p><p></p><p>
The expected salary range for this position based on the primary location of California is $127,800 - $237,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.</p><p></p><p>
Benefits</p><p></p><p>
#LI-JD1</p><p>
#ComputationCoE</p><p></p><p>
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.</p><p></p><p>
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</p></div><p></p>
<div><div>JOB FACTS
</div><div><div><ul><div><b>Job Sub Category</b><b>
</b><p>Computational Biology
</p></div><div><b>Schedule</b><b>
</b><p>Full time
</p></div><div><b>Job Type</b><b>
</b><p>Regular
</p></div><div><b>Posted Date</b><b>
</b><p>May 12th 2026
</p></div><div><b>Job ID</b><b>
</b><p>202605-111673</p></div></ul></div></div></div></div><p></p>

Sr. Data Delivery Specialist (Public and purchased data collection)

UC San Francisco Academic

<div><div><h3 class="jobSectionHeader"><b>Application Window</b></h3>
</div><div><p><b>Open date: </b>May 15, 2026
</p></div><div><p><b>Next review date:</b> Saturday, May 30, 2026 at 11:59pm (Pacific Time)<br>
Apply by this date to ensure full consideration by the committee.
</p></div><div><p><b>Final date: </b>Monday, Nov 15, 2027 at 11:59pm (Pacific Time)<br>
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
</p></div><h3 class="jobSectionHeader"><b>Position description</b></h3>
<div><div><p>L&rsquo;Etoile Lab &ndash; Associate or Full Specialist<br>
Department of Cell &amp; Tissue Biology<br>
UC San Francisco</p>
<p>The candidate for this position is needed to perform basic and translational research studying learning and memory in the context of aging and neurodegeneration. The candidate will be expected to jump into our studies that have identified the role for a highly conserved Transient Receptor Channel (TRP) protein in neuronal plasticity, discovered the neural basis for motor memory and found neural correlates to sleep that decay during aging and predispose to age dependent memory declines. In this Specialist position the candidate will need to: 1) publish current findings, 2) extend existing methods and analyses to new memory paradigms for which this strategy may be useful, and 3) test novel neuromodulation protocols as part of an ongoing collaboration with Drs. Andrei Goga (CTB UCSF) and Miri VanHoven (SJSU)&rsquo;s labs.</p>
<p>Required Qualifications:</p>
<ul><li>Master&rsquo;s degree (or equivalent degree) or five to ten years of relevant research experience to be appointed at the Associate rank.</li>
<li>PhD (or equivalent degree) or ten or more years of relevant research experience to be appointed at the Full rank.</li>
<li>Specialized skills: MatLab proficiency, ITKSnap proficiency, Python proficiency, C. elegans neural ID expertise, and transgenic worm creating and maintenance.
</li></ul><p>Preferred Qualifications:</p>
<ul><li>Ability to perform and troubleshoot C elegans memory training and calcium imaging and PDMS microfluidic device creating (autocad).</li>
</ul>
<p>See Table 24B for the salary range for this position. A reasonable estimate for this position is $75,600-$194,800.</p>
<p>Please click here to apply with CV and contact information for three references. Applicant materials must list current qualifications upon submission.</p>
</div></div>
<h3 class="jobSectionHeader"><b>Application Requirements</b></h3>
<div><div><b>Document requirements</b>
<ul><li><div><p>Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
</p></div></li><li><div><p>Cover Letter (Optional)</p>
</div></li><li><div><p>
Statement of Research (Optional)</p>
</div></li></ul>
</div><div><div><b>Reference requirements</b></div><ul><li>
3 required (contact information only)</li></ul></div>
</div><h3 class="jobSectionHeader"><b>About UC San Francisco</b></h3>
<div>
<div><p>As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
</p><p>The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.</p>
<p>UCSF is committed to welcoming and serving all people, honoring the dignity of every individual without preference or prejudice, in support of its public mission and in alignment with our PRIDE values and Principles of Community.</p>
<div>As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.<br>
<ul><li>&ldquo;Misconduct&rdquo; means any violation of the policies or laws governing conduct at the applicant&rsquo;s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, or discrimination, as defined by the employer.</li><li>UC Sexual Violence and Sexual Harassment Policy</li><li>UC Anti-Discrimination Policy</li><li>APM - 035: Affirmative Action and Nondiscrimination in Employment
</li></ul></div></div></div><h3 class="jobSectionHeader"><b>Job location</b></h3>
<div>San Francisco, CA</div></div>

L’Etoile Lab – Associate or Full Specialist

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 <br/>
 <br/>
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 <strong>
  San Francisco, CA, USA; Reston, VA, USA
 </strong>
 .
 <strong>
  Minimum qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  </li>
  <li>
   3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3 years of experience developing and deploying machine learning and AI models in production settings.
  </li>
  <li>
   Experience at the intersection of security or fraud and ML.
  </li>
  <li>
   Experience applying a variety of unsupervised, semi-supervised, and supervised machine learning techniques, and the ability to turn big data into actionable intelligence.
  </li>
  <li>
   Experience building LLM-powered applications to automate the analysis and contextualization of complex data.
  </li>
  <li>
   Experience with the challenges in applying machine learning in a non-stationary and adversarial environment.
  </li>
  <li>
   Ability to evaluate, analyze, and improve machine learning models and LLM-driven systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 The Google Cloud Gusto AI Data Science Research team develops innovative, data-driven solutions to today&rsquo;s most challenging cybersecurity problems. By leveraging data derived from Google's unparalleled view of the threat landscape, our cross-functional, applied research team experiments and delivers impactful findings for both our customers and the broader cybersecurity industry.
 <br/>
 <br/>
 We are looking for a Research Data Scientist to help us solve challenging cybersecurity problems and protect billions of customers by applying their expert knowledge of machine learning, statistics, and Generative AI. In this role, you will partner with subject matter experts on the front lines defending against advanced threat actors, iteratively develop new capabilities, and work closely with our engineering team to deploy and maintain them. Our team works on a wide variety of cybersecurity challenges including agentic security operations, threat intelligence contextualization, security-tuning LLMs, dark web threat detection, and more. We encourage sharing impactful learnings through publications at academic conferences and talks at industry venues.
 <br/>
 <br/>
 The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 <br/>
 <br/>
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Explore promising areas of future research at the intersection of cybersecurity and machine learning.
  </li>
  <li>
   Drive the research and development of new models and analytic products to solve cybersecurity problems.
  </li>
  <li>
   Develop models and analytics. Move from proof of concept to minimum viable product quickly and efficiently.
  </li>
  <li>
   Work closely with other engineering teams to develop scalable data pipelines, deploy models/analytics, and enact telemetry-driven model improvements over time.
  </li>
  <li>
   Communicate research results to stakeholders and the research community through documentation, white papers, peer-reviewed publications, and presentations.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>


Research Data Scientist, Cybersecurity, Google Cloud

Autopoiesis Sciences

<div>
 <p>
  <strong>
   About The Role
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Autopoiesis Sciences is a San Francisco-based AI lab building systems that can do science autonomously. We are building the architectures, training methods, and reasoning systems that give AI the judgment to pursue discovery on its own, working the full stack from how scientific reasoning is distilled into models to how the research process itself can be made autonomous. We are backed by Informed Ventures, Alpaca VC, and VitalStage Ventures, Adam Grosser, Ally Warson, Hiro Mizushima, Mike Mahklow, Cross Atlantic Angels, and others.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are currently testing a newly trained autonomous AI system across a broad range of real-world tasks and need sharp, curious people to help us do it. Our AI reasons and plans autonomously, then relays instructions to a human operator who executes them across whatever interface the task requires. For the purposes of this research, it is the most direct way to study unconstrained autonomous behavior at the fidelity we need. You are the hands. The AI is the brain. Together, you close the loop.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You'll Be Doing
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Receiving real-time instructions from an autonomous AI system and executing them accurately across whatever interface the task requires
  </li>
  <li>
   Logging outcomes, flagging ambiguities, and providing structured feedback that feeds directly into our research
  </li>
  <li>
   Working alongside ML researchers and engineers to help refine evaluation protocols as the project evolves
  </li>
  <li>
   Participating in debrief sessions where your observations shape how we understand and improve the system
  </li>
  <li>
   Occasionally supporting broader lab operations and research workflows as needed
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Who We're Looking For
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Curious about AI research and autonomous systems, whether through coursework, personal interest, or prior experience
  </li>
  <li>
   No degree required, but a background or active interest in STEM is a plus
  </li>
  <li>
   Comfortable following precise technical instructions quickly and accurately
  </li>
  <li>
   Detail-oriented enough to notice when something unexpected happens and articulate it clearly
  </li>
  <li>
   Interested in how autonomous AI systems actually behave outside of demos and papers
  </li>
  <li>
   Reliable, communicative, and able to work on-site at our SF office and warehouse space
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Compensation and Benefits
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Duration: 3 months with potential for extension
  </li>
  <li>
   Mentorship from researchers and engineers working on autonomous AI systems
  </li>
  <li>
   Collaborate in building a thoughtful, mission-driven team culture focused on autonomous scientific discovery
  </li>
  <li>
   Compensation packages are variable based on experience, expertise, and contribution potential. If your expectations fall outside our stated range, we encourage you to apply regardless. The range for this role is $25/hr-35/hr
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Get To Know Us
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We're a dedicated team of scientists, researchers, and engineers who believe deeply in the transformative potential of our work. You'll work closely with our leadership team including Chief Executive Officer Joseph Reth (Attended University for CS at 14, former DARPA), Chief Business Officer Dr. Eike Gerhardt (University of T&uuml;bingen PhD, University of T&uuml;bingen staff), Chief Scientist Dr. Larry Callahan (University of Chicago PhD, former FDA, former NIH), and VP of Research Vincent Karpf (UC Berkeley).
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Application Process:
  </strong>
  Due to the high volume of automated applications, we only accept applications through LinkedIn as it helps us connect with genuine candidates. We have systems in place to detect automated submissions and strongly advise against using bots or automated tools in your application process. Please be human in your approach.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Equal Opportunity:
  </strong>
  Autopoiesis Sciences, Inc. is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or any other legally protected characteristics.
 </p>
</div>


Human-AI Interface Research Assistant

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