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Bayesian Phd Jobs (NOW HIRING)

Jobtailor

Senior Director, Biostatistics

Cambridge, MA · On-site

$150 - $190/hr

PhD in statistics strongly preferred; Candidates with MS in statistics, biostatistics or ... Advanced knowledge of statistical methods in clinical study designs (adaptive, Bayesian ...

Intuit

Senior Staff AI Scientist

Atlanta, GA · On-site

Qualifications * 6+ years of industry experience with AI science * BS, MS or PhD in Statistics ... Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Atlanta, GA · On-site

Qualifications * 4+ years of industry experience with AI science * BS, MS or PhD in Statistics ... Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

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Bayesian Phd information

What is a Bayesian PhD?

A Bayesian PhD typically refers to an individual who has completed a doctoral program with a focus on Bayesian statistics or Bayesian methods in their research. Bayesian statistics is a branch of statistics that uses probability distributions to represent uncertainty about unknowns, updating beliefs as new data becomes available. Students in this field learn to develop and apply Bayesian models to a wide range of problems in science, engineering, and social sciences. A PhD program with a Bayesian focus often involves advanced coursework in probability theory, statistical inference, and computational methods, as well as original research using Bayesian approaches.

What are the key skills and qualifications needed to thrive as a Bayesian PhD?

To thrive as a Bayesian PhD, you need advanced knowledge of probability theory, statistical inference, and mathematics, typically supported by a doctoral degree in statistics, mathematics, or a related field. Proficiency with statistical programming languages like R, Python, and specialized Bayesian tools such as Stan or BUGS is essential. Strong critical thinking, problem-solving, and clear communication skills help in articulating complex analyses and collaborating across disciplines. These capabilities are crucial for developing rigorous models, conducting impactful research, and translating statistical insights into actionable solutions.

What are some common challenges faced by a Bayesian PhD researcher during collaborative projects?

Bayesian PhD researchers often collaborate with interdisciplinary teams, which can present challenges such as communicating complex statistical concepts to non-specialists and integrating Bayesian methods with other analytical frameworks. Balancing the depth of theoretical work with practical problem-solving, managing computational demands, and aligning project goals with collaborators' expectations are also common hurdles. Successful collaboration typically requires strong communication skills, adaptability, and a willingness to bridge methodological gaps between disciplines.

What is the difference between Bayesian Phd vs Data Scientist?

AspectBayesian PhdData Scientist
Required CredentialsPhD in Statistics, Mathematics, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, academic or specialized industry rolesBusiness-focused, tech companies, or consulting firms
Industry UsageAcademic research, advanced analytics, specialized modelingData analysis, machine learning, business insights
Common Search/ComparisonYesYes

While a Bayesian PhD specializes in advanced statistical modeling and research, a Data Scientist applies data analysis and machine learning techniques in practical business contexts. Both roles require strong analytical skills, but the Bayesian PhD typically focuses on theoretical development, whereas the Data Scientist emphasizes application and implementation.

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Bayesian Phd jobs near you
Infographic showing various Bayesian Phd job openings in the United States as of August 2026, with employment types broken down into 77% Full Time, 21% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution.

Research Scientist Intern, State Estimation for Dexterous Manipulation (PhD)

Meta

Redmond, WA

Internship

Re-posted 6 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

137th of 245 rated software companies

Job description

At Reality Labs Research, our goal is to explore, innovate and design novel interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of natural, seamless experiences in XR environments that are effective, enjoyable, and functionally indistinguishable from those in the real world.As a Research Scientist Intern, you will work at the intersection of representation learning, physics-based estimation, and robotic manipulation. Your primary focus will be on developing latent space representations of object physical state with learned, high-dimensional embeddings that can capture time-varying object properties during dexterous manipulation. You will design experiments to validate these representations and demonstrate their value in practical multi-sensory setup and applications.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, State Estimation for Dexterous Manipulation (PhD) Responsibilities:
  • Design and implement latent space representations for object physical state during robotics manipulation tasks that go beyond fixed parameter sets.
  • Design and execute controlled experiments to validate the representation: measuring adaptation speed, property decoding fidelity, and downstream control performance against baselines (no object state, explicit physical parameters, raw sensor history).
  • Benchmark the latent state representation on practical dexterous manipulation tasks.
  • Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
  • Showcase the value in simulated or physical demos.

Minimum Qualifications:
  • Currently has or is in the process of obtaining a Ph.D. degree in Robotics, Machine Learning, Computer Science, or relevant technical field
  • Strong background in representation learning, generative models, or neural implicit representations (e.g., Gaussian splatting, NeRF, structured latent variable models)
  • Experience with physics-based estimation, state estimation, or system identification in robotic or dynamical systems (e.g. Bayesian filtering, online adaptation, or meta-learning for system identification)
  • Experience with Python and PyTorch
  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:
  • Experience with tactile sensing, force/torque sensors, or robot hand manipulation
  • Familiarity with model-based control (MPC), reinforcement learning, or imitation learning for manipulation
  • Experience with Bayesian filtering, online adaptation, or meta-learning for system identification
  • Experience with experimental design and statistical evaluation of robotic systems
  • Experience working and communicating cross functionally in a team environment
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI), or similar
  • Intent to return to the degree program after the completion of the internship/co-op

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$7,650/month to $12,667/month + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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