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Thesis Work Jobs (NOW HIRING)

Thesis

Retention Product Manager

New York, NY · On-site

$115K - $140K/yr

We can't quantify everything we think you'll love about working at Thesis, from the exciting projects you'll work on, to the smart and humble team you'll get to work with, and our supportive and ...

Thesis

Retention Product Manager

New York, NY

$115K - $140K/yr

We can't quantify everything we think you'll love about working at Thesis, from the exciting projects you'll work on, to the smart and humble team you'll get to work with, and our supportive and ...

Nvidia

Senior Compiler Engineer - Backend

Austin, TX · On-site

Significant academic compiler related project or thesis work * Background in LLVM code generation including instruction scheduling, software pipelining, register allocation, GlobalISel, TableGen ...

SpaceX

Sr. Antenna Engineer (Starship)

Hawthorne, CA

$225K/yr

Master's degree or PhD in electrical engineering with research/thesis work on RF or antennas * Experience with test equipment such as spectrum analyzer, signal generator, network analyzer, power ...

Precise Systems

Mechanical Engineer

Key West, FL · On-site

Bachelors Degree in Mechanical Engineering, Aerospace Engineering, Ocean Engineering, Physics, Materials Science, Chemistry or a related technical field.; with dissertation or thesis work related to ...

Joby Aviation

Loads and Dynamics Engineer

Santa Cruz, CA

$121K - $206K/yr

... or thesis work considered * Solid understanding of aircraft loads fundamentals and aeroelastic principles * Experience with finite element or aeroelastic analysis tools (NASTRAN, Abaqus, ZONA or ...

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Thesis Work information

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How much do thesis work jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for thesis work in the United States is $18.21, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $17.79 per hour, depending on experience, location, and employer.

What are common challenges faced during thesis work in a professional or academic setting, and how can they be managed?

One of the most common challenges in thesis work is managing time effectively, as balancing research, writing, and potential collaboration with advisors or teams can be demanding. Additionally, navigating unclear research objectives or scope can slow progress, so regular check-ins with supervisors and setting clear milestones are crucial. Collaboration with peers and seeking feedback early can also help overcome obstacles and improve the quality of your thesis. Leveraging project management tools and maintaining open communication with your advisor can make the process smoother and more rewarding.

What are the key skills and qualifications needed to thrive in Thesis Work, and why are they important?

To excel in Thesis Work, you need strong research abilities, subject matter expertise, and analytical thinking, usually supported by relevant academic coursework or prior research experience. Familiarity with academic databases, citation management tools (like EndNote or Zotero), and statistical software (such as SPSS or R) is often required. Excellent time management, critical thinking, and written communication skills are essential for producing high-quality academic writing and managing deadlines. These skills ensure the successful completion of a rigorous, original research project that meets academic standards.

What is thesis work?

Thesis work refers to a research project or comprehensive study that students typically undertake as part of the requirements for completing a bachelor's, master's, or doctoral degree. The process involves identifying a research question, conducting an in-depth literature review, gathering and analyzing data, and presenting findings in a formal written document known as a thesis or dissertation. Thesis work demonstrates a student's ability to conduct independent research and contribute original knowledge or insights to their field of study. It often concludes with an oral defense before a panel of experts. Completing thesis work is a significant academic milestone and essential for graduation in many programs.

What is the difference between Thesis Work vs Research Assistant?

AspectThesis WorkResearch Assistant
Required CredentialsTypically graduate-level education, research skillsOften graduate or undergraduate students, research skills beneficial
Work EnvironmentIndependent research, academic settingCollaborative projects, labs or fieldwork
Employer & Industry UsageUniversities, academic researchUniversities, research institutions, labs
Common Search & Comparison IntentUnderstanding academic research roles, thesis requirementsResearch roles, assisting in projects

Thesis Work involves conducting independent research for academic purposes, often as part of a graduate degree. Research Assistants support research projects under supervision, assisting with data collection and analysis. While both roles require research skills and are common in academic settings, Thesis Work is more autonomous and focused on a specific thesis project, whereas Research Assistants work collaboratively on broader research tasks.

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Thesis Work jobs near you
Infographic showing various Thesis Work job openings in the United States as of July 2026, with employment types broken down into 19% Locum Tenens, 5% Full Time, 8% Part Time, 64% Nights, and 4% Summer. Highlights an 36% Physical, 1% Hybrid, and 63% Remote job distribution, with an average salary of $37,874 per year, or $18.2 per hour.

AI Residency Program, Material Science (2026 Cohort)

Lila Sciences

Cambridge, MA • On-site, Remote

Other

Re-posted 17 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