Research Scientist

Job Requisition:

JR101631 Research Scientist (Open)

Job Posting Title:

Research Scientist

Department:

CC00110 WM001 | PROV | Data Science

Job Family:

Staff - Scientist

Worker Sub-Type:

Regular (benefited)

Job Requisition Primary Location:

Integrated Science Center

Primary Job Posting Location:

Posting Location - William & Mary

Job Description Summary:

The Department of Data Science at William & Mary is devoted to the study and application of data-centered approaches to inquiry, analysis, and communication. The department supports students in developing the skills needed to work thoughtfully with data in a range of contexts, including those shaped by emerging tools in artificial intelligence. Through its teaching, scholarship, and mentorship, the department contributes to the liberal education of undergraduates and the training of graduate students. Faculty offer courses, seminars, directed research, and independent study that foster analytical thinking, technical competence, and clear communication, while also encouraging students to consider the ethical and societal dimensions of data-driven and AI-assisted inquiry. The department offers a B.S. in Data Science, a minor in Data Science, and contributes to the advising and mentoring of Ph.D. students.

We seek a highly motivated researcher with expertise in data science, machine learning, and AI for scientific applications, with particular interest in areas such as large language models (LLMs), retrieval-augmented generation (RAG), agentic systems, high-performance computing (HPC), and optimization. Experience in the analysis of experimental nuclear and particle physics data is strongly preferred.
The selected candidate will contribute to the development and deployment of the AID2E (AI-Assisted Detector Design and Optimization Environment) framework, a scalable and distributed platform for AI-driven detector design and optimization in nuclear and particle physics. They will also contribute to the teaching mission of the Department of Data Science, teaching one course in the Spring and Fall semester.

This position will also have a one-course per semester instructional responsibility in the Department of Data Science, with assignments provided by the Chair. This instructional role carries significant responsibilities, and the successful candidate must be prepared to adhere to the policies as outlined in the W&M Faculty Handbook.

This position is based at William & Mary in Williamsburg, Virginia.

Job Description:

Required Qualifications:

• Master’s degree in Computer Science, Data Science, a closely related field, or equivalent combination of education, experience, and training.

• Excellent interpersonal and communication skills with an ability to interact professionally with a diverse group of clients, partners, data users, and staff

• Working knowledge of programming languages (i.e., Python) to retrieve and manipulate large datasets and implement ML and AI workflows.

Preferred Qualifications:

• Ph.D. in Computer Science, Data Science, a closely related field, or equivalent combination of education, experience, and training.

• Experience in the analysis of experimental nuclear and particle physics data.

• Experience working with distributed (multiple computational node) systems.

Conditions of Employment: 

• This is a restricted position subject to availability of funding.

Duties: 

25%- Extending and maintaining distributed AI/ML workflows for detector design and optimization:

• Design, implement, and maintain scalable, distributed machine learning pipelines within the AID2E framework.

• Develop data ingestion, preprocessing, and model training workflows across high-performance computing (HPC) environments.

• Ensure reproducibility, efficiency, and fault tolerance of computational workflows.

• Collaborate with cross-institutional teams to integrate new tools, libraries, and infrastructure components.

• Monitor and optimize system performance, resource utilization, and workflow scalability.

25%- Applying advanced machine learning and multi-objective optimization techniques:

• Develop and deploy state-of-the-art ML models (e.g., deep learning, reinforcement learning) for scientific applications.

• Apply multi-objective optimization methods such as Bayesian optimization and evolutionary algorithms.

• Evaluate model performance using appropriate metrics and validation strategies.

• Conduct sensitivity analyses and uncertainty quantification.

• Contribute to methodological innovation in AI-driven scientific discovery.

25%- Supporting applications to next-generation experiments, including the Electron-Ion Collider:

• Collaborate with physicists and interdisciplinary teams on experimental design and analysis.

• Translate scientific requirements into computational models and AI/ML solutions.

• Contribute to simulation, data analysis, and detector optimization efforts.

• Assist in preparation of technical reports, peer-reviewed publications, and grant proposals.

• Participate in research meetings, workshops, and collaborative initiatives.

18%- Integrating emerging AI paradigms (e.g., agentic workflows) into scientific pipelines:

• Investigate and prototype emerging AI approaches, including LLMs, RAG, and agent-based systems.

• Integrate novel AI methods into existing scientific and computational workflows.

• Explore automation of research lifecycle components (e.g., experiment design, code generation, data interpretation).

• Evaluate reliability, scalability, and performance of new approaches.

7%- Teaching one course each semester within the Department of Data Science:

• Prepare and deliver course materials, including lectures, assignments, and assessments.

• Develop syllabi aligned with departmental curriculum and learning objectives.

• Mentor and support undergraduate and graduate students.

• Facilitate experiential learning opportunities such as projects and independent studies.

• Adhere to university policies and contribute to the teaching mission of the department.

Posting Range: up to $80,000 commensurate with experience

Additional Job Description:

Job Profile:

JP0538 - Scientist I - Exempt - Salary - S11

Qualifications:

Compensation Grade:

S11

Recruiting Start Date:

2026-04-30

Review Date:

2026-05-14

Position Restrictions:

Restricted Funds

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Remote Work Disclaimer: Remote work eligibility is not guaranteed and is subject to approval. Employee eligibility depends on the likelihood of the employee succeeding in a remote work arrangement and the supervisor’s ability to manage remote workers. Departments and/or Human Resources may amend, alter, change, delete, or modify eligibility.