machine learning researcher

Raytheon

<div>Date Posted:
Country:
United Kingdom
Location:
Gloucester, South Gloucestershire
Position Role Type:
Unspecified
Gloucester, London or Manchester
Hybrid role: Must be prepared to work from a Raytheon or customer site depending on demand. Average of 3 days a week on-site.
SC Required
Must already hold or be able to gain an eDV clearance.
Raytheon UK
At Raytheon UK, we take immense pride in being a leader in defence and aerospace technology. As an employer, we are dedicated to fuelling innovation, nurturing talent, and fostering a culture of excellence.
Joining our team means being part of an organisation that shapes the future of national security whilst investing in your growth and personal development. We provide a collaborative environment, abundant opportunities for professional development, and a profound sense of purpose in what we do. Together, we are not just advancing technology; we're building a community committed to safeguarding a safer and more connected world.
About the role:
 
This role is within the Strategic Research Group (SRG). The SRG are a team of Data Science, Machine Learning and AI specialists who develop novel AI solutions to mission focussed problems. In this role you will work with high levels of autonomy and be responsible for the design, planning and technical leadership of multiple AI/ML projects. You will help lead and set technical and strategic direction for the group, support with customer and stakeholder engagement and deliver technical solutions on internal and external projects.
Skills and Experience
Requirements<ul><li>
BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field.</li><li>
Multiple years experience of delivering novel ML solutions to customers and internal stakeholders.</li><li>
Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.</li><li>
Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.</li><li>
Experience of appropriate version control and environment management (such as venvs or Docker).</li><li>
Experience of writing technical project proposals.</li><li>
Experience of managing teams. This can be technical leadership and/or line management.</li><li>
Experience of leading teams following agile principles.</li><li>
Expert knowledge of AI/ML algorithms for different data types and tasks including Generative AI, NLP and computer vision, sufficient to be able to propose research beyond existing literature.</li><li>
Experience of training and developing AI models including Large Language Models.</li><li>
Ability to produce high-quality scientific writing for internal &amp; external stakeholders as well as academic publications.</li><li>
Ability to work with high levels of autonomy, with awareness of appropriate business policies and strategy to dictate your actions.</li></ul>
Desirable
<ul><li>PhD. or Masters degree highlighting experience of academic research.</li><li>
Experience of deploying AI models in a scalable way for external users.</li><li>
Experience developing supporting systems for AI deployments (e.g. backend databases, front end UIs)</li><li>
Working knowledge of Linux systems, using basic commandline functionality (e.g. AWS CLI, Docker CLI, Linux commands like ssh, ls, cd&hellip;)</li><li>
Experience working in Cloud, especially AWS but also equivalents such as GCP or Azure.</li><li>
Research publications in peer reviewed journals.</li><li>
Experience of delivering AI/ML projects in defence or government.</li><li>
Existing network of contacts across defence and government.</li></ul>
Responsibilities
<ul><li>Support the Head of Data Science &amp; Machine Learning using your experience to contribute to the group strategy and stakeholder engagement.</li><li>
Bring ideas for novel research that will drive competitive advantage in across our customer community.</li><li>
Work with autonomy to develop complex, novel data science solutions.</li><li>
Support in triaging and responding to opportunities, aligning to the group and wider business strategies.</li><li>
Design and deliver data-centric solutions while working collaboratively across disciplines.</li><li>
Technical delivery of research and applied AI/ML tasks on both customer and internal research projects.</li><li>
Provide technical leadership across multiple projects.</li><li>
Manage more junior team members across the SRG.</li><li>
Deliver AI/ML/Data Science solutions to broad range of problems in defence.</li><li>
Work with customers and internal stakeholders to determine appropriate technical approaches and do the technical development required for delivery.</li><li>
Excellent communication skills, prepared to present and undertake practical demonstrations of work internally in the team, to senior stakeholders and at conferences with adaptability to audiences of different levels of technical expertise.</li></ul>
Benefits and Work Culture
Benefits<ul><li>
25 days holiday + statutory public holidays, plus opportunity to buy and sell up to 5 days (37hr)</li><li>
Contributory Pension Scheme (up to 10.5% company contribution)</li><li>
Company bonus scheme (discretionary).
</li><li>6 times salary &lsquo;Life Assurance&rsquo; with pension.</li><li>
Flexible Benefits scheme with extensive salary sacrifice schemes, including Health Cashplan, Dental, and Cycle to Work amongst others.</li><li>
Enhanced sick pay.</li><li>
Enhanced family friendly policies including enhanced maternity, paternity &amp; shared parental leave.</li><li>
Private Medical Insurance (dependant on grade)</li></ul>
Work Culture<ul><li>
37hr working week, although hours may vary depending on role, job requirement or site-specific arrangements.</li><li>
Early 1.30pm finish Friday, start your weekend early!</li><li>
Remote, hybrid and site based working opportunities, dependant on your needs and the requirements of the role.</li><li>
A grownup flexible working culture that is output, not time spent at desk, focussed. More formal flexible working arrangements can also be requested and assessed subject to the role. Please enquire or highlight any request to our Talent Acquisition team to explore the flexible working possibilities.</li><li>
Up to 5 paid days volunteering each year.</li></ul>
RTX
Raytheon UK is a landed company and part of the wider RTX organisation. Headquartered in Arlington, Virginia, USA, but with over 180,000 employees globally across every continent, RTX provides advanced systems and services for commercial, military and government customers worldwide and comprises three industry-leading businesses &ndash; Collins Aerospace Systems, Pratt &amp; Whitney, and Raytheon.
Supporting over 35,000 jobs across 13 UK sites, RTX is helping to drive prosperity. Each year our work contributes over &pound;2.7bn to the UK economy and offers a wealth of opportunities to 4,000 suppliers across England, Scotland, Wales and Northern Ireland. We&rsquo;re investing in all corners of the country, supporting 29,040 jobs in England, 3,040 in Northern Ireland, 1,900 in Scotland and 1,600 in Wales.
#LI-VD1
RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.
Privacy Policy and Terms:</div>

Principal Data Scientist & Machine Learning Researcher

New York University Abu Dhabi

<div>
 The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics.
 
 
 
 Skills
 
 
 
 We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include:
 
 
 <ul>
 <li>
 multi-modal learning,
 </li>
 <li>
 foundation models, including large language models,
 </li>
 <li>
 agentic AI,
 </li>
 <li>
 multi-agent AI systems,
 </li>
 <li>
 transfer learning,
 </li>
 <li>
 self-supervised learning,
 </li>
 <li>
 and federated learning.
 
 
 </li>
 </ul>
 The Postdoctoral Researcher will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will engage with our regular collaborators across the NYU campuses and local medical institutions in the UAE.
 
 
 
 Key Responsibilities
 
 
 
 
 Research
 
 
 
 <ul>
 <li>
 Support the supervisor in developing and implementing the research agenda;
 </li>
 <li>
 Conduct high-quality and innovative research primarily focused on ML methodology development for healthcare;
 </li>
 <li>
 Generate new high-impact ideas based on gaps and limitations of the state-of-the-art (SOTA);
 </li>
 <li>
 Design and implement experiments to compare proposed work with SOTA baselines;
 </li>
 <li>
 Publish research findings in high-impact journals and conferences;
 </li>
 <li>
 Communicate and present research findings at international academic gatherings;
 </li>
 <li>
 Create, maintain, and document high-quality research code for reproducibility;
 </li>
 <li>
 Maintain good practice in managing and accessing sensitive medical datasets;
 </li>
 <li>
 Assist the supervisor in the preparation of grant applications (as appropriate);
 </li>
 <li>
 And collaborate with scientists within the NYU Global Network and in Abu Dhabi.
 
 
 </li>
 </ul>
 
 Training &amp; professional development*
 
 
 
 <ul>
 <li>
 Attend trainings and workshops for career development;
 </li>
 <li>
 Mentor PhD students and undergraduate research assistants (as appropriate);
 </li>
 <li>
 Actively participate in events and committees at NYU Abu Dhabi, such as the Postdoctoral Council Steering Committee;
 </li>
 <li>
 Gain experience in applying for local research grants (subject to eligibility);
 </li>
 <li>
 And transition to independence to pursue a career of choosing following the appointment.
 </li>
 <li>
 The researcher will create a personalized training and development plan with the supervisor.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree)
 </li>
 <li>
 Doctoral research in the area of machine learning and artificial intelligence
 </li>
 <li>
 Bachelor&rsquo;s/ Master&rsquo;s degree in computer science, mathematics, computer engineering, or relevant technical field
 </li>
 <li>
 First-author peer-reviewed published papers (or under review)
 </li>
 <li>
 Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) with several years of practice
 </li>
 <li>
 Experience in maintaining high-quality code on Github
 </li>
 <li>
 Experience in running and managing experiments using GPUs
 </li>
 <li>
 Ability to visualize experimental results and learning curves
 </li>
 <li>
 Effective inter-personal and team-building skills
 </li>
 <li>
 Self-motivated with an ability to work independently and in a team to get the work done
 </li>
 <li>
 Excellent communication skills (oral and written communication)
 </li>
 <li>
 Willingness to learn and confront new challenges
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Doctoral research conducted in the area of machine learning for healthcare and related topics
 </li>
 <li>
 Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning.
 </li>
 <li>
 Experience in dealing with large medical datasets (e.g., electronic health records data or medical images)
 </li>
 <li>
 Ability to use high performance computing cluster
 
 
 </li>
 </ul>
 For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, research statement (1-page), project proposal summary (1-page), a transcript or degree, and three letters of reference, all in PDF format. If you have any questions, please email Prof. Farah Shamout at farah.shamout@nyu.edu.
 
 
 The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled.
 
 
 
 About NYU Abu Dhabi
 
 
 
 https://nyuad.nyu.edu/en/
 
 
 NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity&rsquo;s shared challenges. NYU Abu Dhabi&rsquo;s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.
 
 
 NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.
 
 
 Students are drawn from among the world&rsquo;s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed.
 
 
 
 Working for NYUAD
 
 
 
 At NYUAD, we recognize that Abu Dhabi is more than where you work; it&rsquo;s your home. In order for research staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to research staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents.
 
 
 NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community.
 
 
 Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply.
 
 
 
 Join NYU Abu Dhabi, an exceptional place for exceptional people.
 
 
 
 NYUAD values belonging and respect; such principles are fundamental to the university&rsquo;s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University&rsquo;s mission.
 
 
 @WorkAtNYUAD
 
 
 
 Equal Employment Opportunity Statement
 
 
 
 
 For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
 
 
 
 NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
 
 
 
 Sustainability Statement
 
 
 
 NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability
</div>

Post-Doctoral Associate in the Division of Engineering (Electrical and Computer Engineering) - Dr. Farah Shamout

TU Delft

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Postdoc Trustworthy Graph Machine Learning
Trustworthy Graph Machine Learning for Population Scale Networks
Job description
We invite applications for a postdoctoral researcher to work on fundamental techniques for trustworthy graph machine learning for the analysis of population-scale networks. The position focuses on two pillars of trustworthiness: explainability and privacy-preserving learning.
This research direction connects closely to ongoing work by Dr. Megha Khosla on trustworthy graph machine learning, especially on the relationship between transparency and privacy in graph-based models. Population-scale network data are highly relational and often sensitive. Graph models for such data must therefore be accurate, interpretable and designed to reduce privacy risks.
A central aim of the position is to develop explainability methods for graph machine learning as a form of decision support. These methods should help researchers understand both model behaviour and the underlying data. They should explain why a model makes a prediction, what structural or demographic patterns the model captures, and when its decisions are reliable enough to support scientific interpretation or decision-making.
At the same time, explanations and learned graph representations can themselves reveal sensitive information. In population-scale networks, privacy risks may arise from rare individuals, sensitive attributes, neighbourhood structures etc.The postdoc will therefore investigate how explanations and graph learning methods can be made privacy-aware. This may include studying privacy risks in develoed models, designing explanations that avoid unnecessary disclosure, or developing new privacy-preserving graph learning techniques.
The project is funded by Macroscope, a Dutch national research infrastructure for studying social change, misinformation and trust at population scale.
We are especially interested in candidates with strong expertise in either explainable graph machine learning or privacy-preserving graph learning, together with a willingness to collaborate across the other area.
You will work with the task PI, Dr. Megha Khosla, and her team of PhD and Master&rsquo;s students. You will also collaborate with scientists from different fields across the Macroscope project, including computer science and computational social science. You will also get opportunities to expand your research network within the Computer Science departments and across the broader TU Delft research community.
Job requirements
PhD in computer science, AI, machine learning, data science, network science, computational social science, or a related field.
Expertise in either explainable graph machine learning or privacy-preserving graph learning.
Willingness to develop expertise across the other area.
Strong programming skills in Python, with experience using tools such as PyTorch, PyTorch Geometric, DGL, NetworkX, or scikit-learn.
Engineering skills and willingness/patience to work with large, noisy datasets, including preprocessing, pipeline development, and scalable evaluation.
Ability to work in an interdisciplinary team and communicate research clearly in English.
TU Delft (Delft University of Technology)
Working at TU Delft means contributing to solutions that really make a difference.
For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.
At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.
Faculty of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment &ndash; which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
, Mathematics and Computer Science.
Conditions of employment
Duration of contract is 2 years Temporary
A job of 38 hours per week.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
An excellent pension scheme via the ABP.
The possibility to compile an individual employment package every year.
Discount with health insurers on supplemental packages.
Flexible working week.
Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
Plenty of opportunities for education, training and courses.
Partially paid parental leave
Attention for working healthy and energetically with the vitality program.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. .
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Megha Khosla, via m.khosla@tudelft.nl.
Application procedure
Are you interested in this vacancy? Please apply no later than 26 July 2026 upload the following documents:
CV
Motivational letter
Research statement describing your own ambitions for the research line you would like to pursue, and explaining how this position would help you develop and achieve those ambitions.
You can address your application to Dr. Megha Khosla.
Please note:
You can apply online. We will not process applications sent by email and/or post.
As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
Please do not contact us for unsolicited services.
 <div><div><div><div><div>Faculty/Department: Faculty of Electrical Engineering, Mathematics &amp; Computer Science
</div></div></div></div><div><div><div><div>Salary range: &euro;3546 - &euro;5538
</div></div></div></div><div><div><div><div>Hours per week: 38
</div></div></div></div><div><div><div><div>FTE: 1
</div></div></div></div><div><div><div><div>Submission is possible until: 26 Jul 2026
</div></div></div></div><div><div><div><div>ID job: 3547
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Postdoc Trustworthy Graph Machine Learning

Achira

<div><h1 class="jobSectionHeader">Why Achira</h1>
At Achira, we are building a team of world-class scientists, ML researchers, and engineers to work together to move beyond the beaten path in drug discovery. We are actively exploring the next frontier of model architectures for AI x Chemistry: developing world models for the physical microcosm. Our goal is to make biology at the molecular level something that can be learned, predicted, and designed.
At Achira, you&rsquo;ll operate at the frontier scale of massive compute, massive data, and massive ambition. You&rsquo;ll own impactful work end-to-end, from ideation to architecture to deployment on distributed infrastructure. We are a well-funded, talent-dense organization that values rigor, speed, execution, and an ownership mindset. We&rsquo;re looking for new members who share our sense of relentless urgency and are natural collaborators who value team success.<h1 class="jobSectionHeader">
About the Role</h1>
We&rsquo;re looking for machine learning researchers who want to shape the frontier of generative models for the atomistic microcosm. You will work at the intersection of cutting-edge machine learning, statistical mechanics, and approximate bayesian inference to help us conquer sampling problems at light-speed. In addition, you&rsquo;ll collaborate with experts in chemistry and physics to invent and implement models to unlock what&rsquo;s possible for Achira&rsquo;s microscopic world models.
While we prefer candidates willing to work from our San Francisco office, highly skilled candidates may be considered for working from New York City with travel to San Francisco as needed. Both locations are offered as hybrid roles, spending at least some of your time working from the office in collaboration with coworkers. Travel is part of all roles at Achira, both to conferences and corporate on-site activities.<h1 class="jobSectionHeader">
What You&rsquo;ll Do</h1><ul><li>
Invent advanced sampling and simulation methods that integrate probabilistic inference, deep learning, and reinforcement learning to enable efficient exploration and simulation of learned energy landscapes for molecular systems.</li><li>
Design and train frontier generative models: diffusion, autoregressive, flow-based, and latent-variable architectures.</li><li>
Build models that can map between data distributions to bridge the gap between simulation and reality.</li><li>
Prototype, benchmark, and iterate rapidly to transform research ideas into reusable and scalable components across Achira&rsquo;s ecosystem.</li><li>
Collaborate with physicists and chemists to ensure models are grounded in real physics.</li><li>
Work with research engineers and the infrastructure team to identify where research ideas will need support in order to deliver effective results.</li></ul><h1 class="jobSectionHeader">
About You</h1><ul><li>
Interested in building generative models that describe real matter.</li><li>
Drive to build at the frontier of what&rsquo;s possible and try out new, high-risk ideas.</li><li>
Machine learning researcher with professional experience (post-degree) in an industry setting.</li><li>
Demonstrated research impact through conference talks or publications (in machine learning venues), open-source contributions, or released models.</li><li>
Strong interdisciplinary communication and presentation skills and the ability to translate ideas and concepts to colleagues from non-ML backgrounds.</li><li>
Proficiency in Python and modern ML frameworks (PyTorch, JAX).</li><li>
Experience collaborating on research projects across multi-person teams.</li></ul><h1 class="jobSectionHeader">
Nice to Have</h1>
Achira values excellent ML researchers from many backgrounds, and expect members of the team to contribute complementary strengths. If the work excites you, we encourage you to apply, even if you hit none of the bonus features listed below!<ul><li>
Experience working with models that operate on 3-D point clouds and dynamic data.</li><li>
Experience in sequential monte carlo methods.</li><li>
Experience with probabilistic programming.</li><li>
Experience with pre-training, mid-training, and post-training (especially reenforcement learning) parts of the model development process.</li><li>
Familiarity with statistical mechanics: working knowledge of sampling, estimators, and the Crooks/Jarzynski perspective of nonequilibrium statistical mechanics.</li><li>
Prior experience working in or with researchers in the domains of computational chemistry, biology, or materials science.</li><li>
Experience working with multi-cloud distributed compute systems.</li><li>
Experience working with multi-site distributed company team.</li></ul>
Compensation Range: $164,638 - $259,000</div>

ML Research Scientist (MLRS) - Generative AI

<div><h1 class="jobSectionHeader">Why Achira</h1>
At Achira, we are building a team of world-class scientists, ML researchers, and engineers to work together to move beyond the beaten path in drug discovery. We are actively exploring the next frontier of model architectures for AI x Chemistry: developing world models for the physical microcosm. Our goal is to make biology at the molecular level something that can be learned, predicted, and designed.
At Achira, you&rsquo;ll operate at the frontier scale of massive compute, massive data, and massive ambition. You&rsquo;ll own impactful work end-to-end, from ideation to architecture to deployment on distributed infrastructure. We are a well-funded, talent-dense organization that values rigor, speed, execution, and an ownership mindset. We&rsquo;re looking for new members who share our sense of relentless urgency and are natural collaborators who value team success.<h1 class="jobSectionHeader">
About the Role</h1>
We&rsquo;re looking for deep learning researchers who want to build rich representations of atomistic systems to help teach AI about the microscopic world. You will collaborate with domain experts in molecular modeling to develop Achira&rsquo;s next-generation foundation models. You&rsquo;ll work at the intersection of model architecture, data, and training strategy to find new points on the Pareto frontier of accuracy and speed for microscale world models.
While we prefer candidates willing to work from our San Francisco office, highly skilled candidates may be considered for working from New York City with travel to San Francisco as needed. Both locations are offered as hybrid roles, spending at least some of your time working from the office in collaboration with coworkers. Travel is part of all roles at Achira, both to conferences and corporate on-site activities.<h1 class="jobSectionHeader">
What You&rsquo;ll Do</h1><ul><li>
Build a robust pre-, mid-, and post-training curriculum that ensures foundation model performance and impact.</li><li>
Create reenforcement learning strategies to help models focus their capacity where it matters most, especially when the training data doesn&rsquo;t cover the domain of applicability.</li><li>
Develop expressive representations of molecular and atomistic structure and dynamics, including equivariant graph neural networks, geometric transformers, and latent encoders that capture physical symmetries and constraints.</li><li>
Prototype, benchmark, and iterate rapidly to transform research ideas into reusable and scalable components across Achira&rsquo;s ecosystem.</li><li>
Collaborate with physicists and chemists to ensure models are grounded in real physics.</li><li>
Work with research engineers and the infrastructure team to identify where research ideas will need support in order to deliver effective results.</li></ul><h1 class="jobSectionHeader">
About You</h1><ul><li>
Drive to apply modern ML techniques to solve problems at the frontier of the microscopic world.</li><li>
A willingness to follow the data and embrace an empirical approach to the bitter lesson.</li><li>
A pragmatic approach to inductive bias (eg. physical priors, equivariance) in model building.</li><li>
Experience designing, running and analyzing ML experiments at scale.</li><li>
Experience with 3D geometric deep learning.</li><li>
Machine learning researcher with professional experience (post-degree) in an industry setting.</li><li>
Demonstrated research impact through conference talks or publications (in machine learning venues), open-source contributions, or released models.</li><li>
Strong interdisciplinary communication and presentation skills and the ability to translate ideas and concepts to colleagues from non-ML backgrounds.</li><li>
Proficiency in Python and modern ML frameworks (PyTorch, JAX).</li><li>
Experience collaborating on research projects across multi-person teams.</li></ul><h1 class="jobSectionHeader">
Nice to Have</h1>
Achira values excellent ML researchers from many backgrounds, and expect members of the team to contribute complementary strengths. If the work excites you, we encourage you to apply, even if you hit none of the bonus features listed below!<ul><li>
Experience with self-supervised representation learning techniques.</li><li>
Experience with Bayesian deep learning techniques and uncertainty quantification.</li><li>
Experience developing or applying generative models for 3D systems.</li><li>
Experience with equivariant graph neural network architectures (NequIP, MACE, SchNet, PaiNN, or similar).</li><li>
Prior experience working in or with researchers in the domains of computational chemistry, biology, or materials science.</li><li>
Experience working with multi-cloud distributed compute systems.</li><li>
Experience working with multi-site distributed company team.</li></ul>
Compensation Range: $164,638 - $259,000</div>

ML Research Scientist (MLRS) - Representation Learning for Molecular AI

Mayo Clinic

<div><div>Why Mayo Clinic</div><div> 
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News &amp; World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans &ndash; to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.</div><div> 
</div><div>
Benefits Highlights 
<ul><li>
Medical: Multiple plan options.</li><li>
Dental: Delta Dental or reimbursement account for flexible coverage.</li><li>
Vision: Affordable plan with national network.</li><li>
Pre-Tax Savings: HSA and FSAs for eligible expenses.</li><li>
Retirement: Competitive retirement package to secure your future.</li></ul></div> 

Responsibilities 
We are seeking a highly motivated researcher with experience in machine learning with Python to develop multimodal AI/ML models from healthcare conversations combined with other sources of data (e.g., scans and tabular data). The ideal candidate will have hands-on experience with textual (NLP), acoustic (speech), and visual data and the ability to integrate these modalities into state-of-the-art models for healthcare applications. The analyst assists with multidisciplinary research analysis using a variety of analytical, quantitative, qualitative, and programming skills. The analyst conducts comprehensive literature searches related to health services research initiatives and compiles and summarizes written and electronic data for research projects. Research funding sources and collects necessary documents for participating in external research collaborations. Writes draft reports that clearly and concisely summarize and illustrate projects findings, outcomes, and results. Drafts sections of grants, abstracts, and manuscripts. Collects and assists in designing data analysis strategies, evaluating data needs and methods of data collection. Implements the data collection protocol. Assists in reviewing study methods, statistical models, and sampling schemes. Trends data to identify potential areas of the investigation supported by graphical presentations. Evaluates the reliability of data sources to ensure data integrity. Coordinates multiple project assignments and is responsible for completing tasks in given timeline. Designs and maintains quantitative and qualitative databases including the management and updating of data.
Model Development &amp; Optimization:<ul><li>
Build and deploy multimodal AI/ML models integrating textual, acoustic, and visual inputs from healthcare conversations and other sources of data (e.g., scans and tabular data)</li><li>
Implement, train, and fine-tune models in Python using packages such as PyTorch, Transformers, OpenCV, torchvision, and torchaudio.</li><li>
Apply prompting strategies, parallel computing, and GPU acceleration to optimize large-scale model training and inference.</li></ul>
Data Management &amp; Analysis:<ul><li>
Collect, preprocess, and manage complex quantitative and qualitative datasets while ensuring data integrity and reproducibility.</li><li>
Design and execute advanced data analysis strategies, including statistical modeling, sampling schemes, and evaluation of computational methods.</li></ul>
Research &amp; Writing:<ul><li>
Conduct literature reviews on AI in healthcare and health services research.</li><li>
Prepare clear and concise reports, visualizations, and presentations of project outcomes.</li><li>
Draft sections of grants, abstracts, and manuscripts related to AI/ML in healthcare.</li><li>
Identify external funding opportunities and contribute to multi-institutional research collaborations.</li></ul>
Project Coordination:<ul><li>
Manage multiple concurrent assignments, track milestones, and ensure timely project delivery.</li><li>
Maintain and update internal quantitative and qualitative databases</li></ul> 

Qualifications 
Master&rsquo;s degree in Computer Science, Engineering, Data Science, Health Informatics, or related field, with substantive coursework in machine learning experience preferred (two years minimum) OR Bachelor&rsquo;s degree in the fields above with strong quantitative background and four years of experience (minimum) required. Research experience preferred. Experience with previous research projects with quantitative and/or qualitative focus. Competent to work independently in most phases of research analysis, requiring only general instructions and direction. Demonstrated proficiency in written communication and research methodology. Able to think logically and to systematically analyze alternative solutions in problem solving. Knowledgeable about a current health care delivery environment. Works with general supervision; develops procedures for performance of a variety of duties; performs complex duties within established guidelines.
Technical Skills:<ul><li>
Strong programming skills in Python, with proficiency in PyTorch, Transformers, and scikit-learn.</li><li>
Experience in NLP, speech processing, and/or visual modeling evidenced through previous projects.</li><li>
Familiarity with GPU computing, distributed training, and prompting strategies ( for large language models.</li><li>
Familiarity with Bash scripting</li></ul>
Professional Skills:<ul><li>
Demonstrated ability to work independently and in multidisciplinary teams.</li><li>
Excellent written and verbal communication skills, with experience drafting research reports and manuscripts.</li><li>
Familiarity and interest with healthcare research and delivery contexts preferred.</li></ul>
Note: Visa sponsorship is not available for this position. Must be U.S. citizen, permanent resident, refugee or asylee. 
Exemption Status 
 
Nonexempt 
 
Compensation Detail 
 
$35.45-$53.15/hr; Education, experience and tenure may be considered along with internal equity when job offers are extended. 
 
Benefits Eligible 
 
No 
 
Schedule 
 
Part Time 
 
Hours/Pay Period 
 
Varied 
 
Schedule Details 
 
Flexible hours/Up to 40 hours a week 
 
Weekend Schedule 
 
N/A 
 
International Assignment 
 
No 
 
Site Description 
<div>
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.</div><div><div> 
Equal Opportunity</div><div> 
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the &quot;EOE is the Law&quot;. Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization. 
</div></div> 
 
Recruiter 
 
Stephanie Baird</div>

KER Unit - Health Services Analyst - Supplemental

Lincoln University

<div>PURPOSE:
The Postdoctoral Research Associate in AI/Machine Learning (AI/ML) will lead advanced analytical, AI/ML, and data science components of a USDA-funded forest farming project. The position will develop and apply state-of-the-art AI/ML methods to survey data to improve understanding of farmer behavior, forest farming adoption, and network development, and will contribute to capacity-building, and outreach activities that strengthen data-driven forest farming and agroforestry decision-making at Lincoln University and across Missouri.
ESSENTIAL JOB FUNCTIONS, DUTIES, &amp; RESPONSIBILITIES:<ul><li>
List essential job functions, duties &amp; responsibilities for the role. Try to be as detailed as possible.</li><li>
Design, implement, and validate machine learning models (random forests, support vector machines, neural networks) for survey nonresponse, response propensity estimation, and weighting adjustments using statewide farmer, landowner, and stakeholder survey data.</li><li>
Build AI/Natural Language Processing (NLP) pipelines (including large language models) to analyze open-ended survey and focus group data and predict farmer knowledge, attitudes, and adoption willingness.</li><li>
Apply multivariate and dimensionality-reduction techniques (PCA, Kernel-PCA, feature selection) to complex, mixed-type datasets.</li><li>
Integrate quantitative survey data (Likert-scale, categorical, and continuous variables) with qualitative and text-derived features to build predictive models of forest farming adoption, perceived barriers, and support needs among socially disadvantaged and resource-limited farmers.</li><li>
Translate analytical findings into outreach strategies, educational materials, economic analysis inputs, and policy recommendations.</li><li>
Prepare technical documentation, reproducible pipelines, and interpretation reports for technical and non-technical audiences.</li><li>
Develop and deliver educational modules, short courses, and training materials on AI/ML, data science, and cloud-based analytics (Google Cloud, no-code ML tools) for non-coding students, extension professionals, and farmers, with a strong emphasis on agriculture- and agroforestry-relevant applications.</li><li>
Contribute to evaluation metrics and grant deliverables (reports, model portfolios, AI/NLP frameworks, outreach summaries, policy documents).</li><li>
Lead or co-author peer-reviewed papers, conference presentations, and extension publications.</li><li>
Mentor graduate and undergraduate students on survey, qualitative, and data science tasks.</li></ul>
QUALIFICATIONS:<ul><li>
List mandatory qualifications.</li><li>
Ph.D. in Statistics, Data Science, Agricultural or Environmental Data Science, Quantitative Social Science, or a closely related field.</li><li>
Experience in developing and applying machine learning models (such as random forests, support vector machines, and neural networks) to empirical datasets.</li><li>
Experience with handling survey or social science data (e.g., Likert scales, categorical responses, mixed methods) and performing statistical modeling or ML-based analysis.</li><li>
Demonstrated competence in at least one major programming language used for data science (R or Python) and in statistical/ML software workflows.</li><li>
Record of peer-reviewed publications.</li><li>
Eligibility to work in the United States for the duration of the appointment.</li></ul>
PREFERRED QUALIFICATIONS:<ul><li>
List any preferred / optional qualifications for this role.</li><li>
Prior research experience in agriculture, forestry, agroforestry, environmental science, or related fields, especially projects involving farmers or landowners.</li><li>
Experience applying AI/ML methods to survey data for nonresponse adjustment, propensity weighting, or behavioral prediction.</li><li>
Background in NLP or text analytics, including work with open-ended survey responses, interviews, or focus group transcripts.</li><li>
Experience designing or delivering educational content on AI/ML, data science, or cloud computing (e.g., short courses, workshops, online modules) for non-coding or mixed-expertise audiences.</li><li>
Familiarity with cloud computing platforms (Google Cloud, AWS) for data analysis and ML model deployment, including use of no-code or low-code tools and AutoML services.</li><li>
Demonstrated interest or experience in community-engaged scholarship, extension, or citizen science, especially with underserved or socially disadvantaged farming populations.</li></ul>
PHYSICAL DEMANDS:<ul><li>
List physical demands as necessary. If none, describe the environment the employee will be working in, i.e. This position will work in an office environment with minimal exposure to physical work.</li><li>
This position will work primarily in an office environment.</li><li>
Occasional travel may be required for project meetings, workshops, field days, or outreach events at Lincoln University facilities, partner institutions, and community sites across Missouri.</li></ul>
This job description is not intended to be a complete list of all responsibilities, duties or skills required for the job and is subject to review and change at any time, with or without notice, in accordance with the needs of Lincoln University. Since no job description can detail all the duties and responsibilities that may be required from time to time in the performance of a job, duties and responsibilities that may be inherent in a job, reasonably required for its performance, or required due to the changing nature of the job shall also be considered part of the jobholder's responsibility.</div>

Postdoctoral Research Associate in AI/Machine Learning

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