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Summer Masters Computer Science Jobs in Boston, MA

MORSE Corp

Data Scientist

Cambridge, MA · On-site

Security Clearance • Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field • 5+ years of experience in ...

Inmar

Director, Data Science (MarTech)

Boston, MA · On-site

Bachelors in Computer Science, Statistics or any related field with an applied quantitative and experimentation focus required * Masters in quantitative and experimentation focused field preferred

Manulife and John Hancock

Data Scientist

Boston, MA · On-site

Masters or equivalent experience in a quantitative field (Computer Science, Mathematics, Physics, Machine Learning, AI, Statistics, or related field) * Knowledge and expertise with SQL with Oracle ...

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All JobsSummer Masters Computer Science JobsSummer Masters Computer Science Jobs in Boston, MA

Summer Masters Computer Science information

What is the difference between Summer Masters Computer Science vs Summer Data Science Intern?

AspectSummer Masters Computer ScienceSummer Data Science Intern
Required CredentialsUndergraduate or Master's in Computer Science or related fieldUndergraduate or Master's in Data Science, Computer Science, or related field
Work EnvironmentSoftware development, coding, algorithm designData analysis, modeling, statistical programming
Employer & Industry UsageTech companies, software firms, startupsTech companies, finance, healthcare, consulting

Summer Masters Computer Science roles focus on software development, coding, and algorithms, while Summer Data Science Intern positions emphasize data analysis, statistical modeling, and data-driven decision making. Both roles typically require similar educational backgrounds and are found in tech-driven industries, but they differ in daily tasks and skill emphasis.

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Summer Masters Computer Science jobs near you

AI Residency Program, Material Science (2026 Cohort)

Lila Sciences

Cambridge, MA • On-site, Remote

Other

Re-posted 11 days ago

Job description

AI Resident - 2026 Cohort

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

  • Duration: 6-12 months (extension possible)
  • Start Dates: First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
  • Cohort Size: Small group of selected residents
  • Mentorship: Pairing with technical mentors, feedback from cross-functional teams
  • Resources: Access to proprietary datasets, high-performance compute, and Lila's research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

 
Application Requirement:
Please submit your resume alongside a research proposal (up to 3 pages, unlimited references) outlining the project you would plan to pursue during your residency at Lila Sciences. Please submit your research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials (e.g., recommendation letters, publications, research artifacts) may also be included. 

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila's world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact. Publishing is encouraged but not required - what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

  • Design and execute independent research projects in AI for materials science
  • Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
  • Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
  • Contribute to collaborative team research and co-develop novel approaches to scientific discovery
  • Share findings internally and externally; publications are welcome but not mandatory

What You'll Need to Succeed

  • Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor's, Master's, or PhD)
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch)
  • Experience working with large-scale datasets or simulations
  • Familiarity with modern AI/ML architectures and training techniques
  • Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

  • Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
  • Familiarity with Bayesian optimization, active learning, or generative models
  • Experience in reinforcement learning or agent-based approaches to scientific reasoning
  • Open-source contributions or collaborative research experience
  • Strong communication and writing skills, especially for conveying complex scientific ideas

Apply