Research Scientist Jobs

Yes, for nearly all positions. Industry research labs and academic institutions expect PhDs demonstrating ability to conduct independent research, formulate novel problems, and contribute original work to the field. Master's-level researchers occasionally get hired for more applied research engineering roles, but these are typically titled differently.

The PhD provides essential training in research methodology, reading and critiquing literature, designing experiments, and communicating results. More importantly, your PhD work serves as evidence of research taste and ability. Publications at conferences like RSS, ICRA, CoRL, or NeurIPS significantly strengthen your position.

Exceptional cases exist where researchers without PhDs contribute significantly to robotics research through industry work or open-source projects, but these are rare. If you're serious about a research career in robotics, expect to invest 4-6 years in doctoral training.

Industry research offers higher compensation, better computational resources, and access to proprietary datasets or robotic platforms. You'll work on problems aligned with company interests, though good labs provide significant research freedom. Publication is valued but product impact may matter equally or more. Equity compensation can be substantial at successful companies.

Academic positions provide tenure-track stability, complete research autonomy, and ability to pursue any problem that interests you. You'll advise students, write grants, and balance research with teaching. Compensation is lower but job security is higher after tenure. Publication record is paramount for career advancement.

Many researchers move between both worlds. Early career scientists often start in industry for higher pay and resources, then move to academia for autonomy. Others go the reverse direction to access better platforms or escape grant-writing. Some maintain industry affiliations while holding academic positions. The boundary is increasingly permeable.

You identify important unsolved problems, design approaches to solve them, implement algorithms, run experiments, analyze results, and publish findings. Daily work involves reading papers to understand the state of the art, writing code to implement new methods, running experiments often in simulation, debugging why approaches fail, and writing papers or reports documenting your work.

In industry, you'll collaborate with product teams to identify research directions with potential impact, work with engineers to transfer research into production systems, and present findings internally and at conferences. In academia, you'll additionally advise graduate students, write grant proposals, teach courses, and serve on committees.

The work requires patience since research rarely proceeds linearly. You'll spend weeks implementing an approach that fails, backtrack to try different formulations, and iterate until finding something that works. Success means advancing understanding in your area, not necessarily shipping products, though applied research roles increasingly value both.

Deep knowledge of machine learning is essential, including understanding of optimization, probabilistic inference, and learning algorithms relevant to robotics. Strong programming skills in Python for implementation and experimentation are required. Many positions also expect C++ capability for performance-critical code or real-time systems.

Experience with simulation tools like Isaac Sim, MuJoCo, or custom simulators matters significantly since modern robotics research relies heavily on simulation. Familiarity with PyTorch or JAX is nearly universal for learning-based approaches. Understanding of reinforcement learning, computer vision, or control theory depends on your research area.

Beyond technical skills, you need strong writing ability to communicate research clearly, presentation skills for conferences and internal talks, and research taste to identify problems worth solving. Publication record at top-tier venues demonstrates these abilities. Open-source contributions and reproducible research practices strengthen your candidacy significantly.

Large tech companies maintain robotics research labs. Amazon has 27 open positions across manipulation, warehouse robotics, and autonomous systems. Meta, Toyota Research Institute, and autonomous vehicle companies invest heavily in research. Industrial robotics companies like ABB and Boston Dynamics also maintain research teams.

Academic institutions worldwide hire robotics faculty and research scientists. Major programs exist at MIT, CMU, Stanford, Berkeley, ETH Zurich, TU Munich, and universities across Asia. Postdoctoral positions provide training before tenure-track faculty roles. National labs like NASA Jet Propulsion Laboratory also conduct robotics research.

Newer AI labs like Anthropic, OpenAI, and Google DeepMind increasingly work on robotics problems, particularly foundation models for robotics and embodied AI. Well-funded startups occasionally hire research scientists for moonshot projects, though these positions are rarer and riskier.

Based on 146 industry job postings, median salaries reach $174,400 annually. Fresh PhDs entering industry research typically start around $113,280. Senior research scientists with strong publication records and research impact earn $205,200 or more, with total compensation reaching $300,525 at top-tier companies when equity is included.

Academic salaries follow different scales. Assistant professors typically earn $80K-$120K depending on institution prestige and location. Associate and full professors reach $120K-$180K, with elite institutions paying more. Academic compensation includes benefits like tenure security, sabbaticals, and research freedom that don't translate directly to salary numbers.

Geographic location affects industry compensation significantly. Bay Area and Seattle positions pay 30-40% more than similar roles elsewhere. Academic salaries vary less geographically but cost of living in university towns affects real compensation substantially.