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Postdoctoral In Bayesian Statistics Jobs Near Me

Ohio State University

Postdoctoral Scholar

Columbus, OH · On-site

$65K - $68K/yr

Postdoctoral Scholar Department:Arts and Sciences | Astronomy The Postdoctoral Scholar will work ... Experience in statistical analysis, machine learning, and data-driven modeling applied to large ...

Ohio State University

Postdoctoral Scholar

Columbus, OH · On-site

$65K - $68K/yr

Postdoctoral Scholar Department:Arts and Sciences | Astronomy Post Doctoral Scholar will work with ... Expertise in statistical analysis, machine learning, and data-driven modeling applied to large ...

micro1 AI

AI Training Specialist - Physics

Columbus, OH · On-site +1

$80 - $150/hr

... Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the ... Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum ...

Ohio State University

Post Doctoral Scholar

Columbus, OH · On-site

$47K - $64K/yr

Arts and Sciences | Psychology Ohio State University Postdoctoral Scholar in Extremism and ... Proficiency in statistical software (e.g., R, SPSS, Python) and survey tools (e.g., Qualtrics)

Ohio State University

Post Doctoral Scholar

Columbus, OH · On-site

$47K - $64K/yr

The postdoctoral associate will have flexibility in choosing their topic(s) of interest. The ... Demonstrated expertise in quantitative data analysis, including advanced statistical modeling (e.g ...

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How much do postdoctoral in bayesian statistics jobs pay per year?

As of Sep 14, 2026, the average yearly pay for postdoctoral in bayesian statistics in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

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Postdoctoral In Bayesian Statistics jobs near you
A map of the United States highlighting the number of Postdoctoral In Bayesian Statistics job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Postdoctoral In Bayesian Statistics job openings in each state, with California having the most at 2 and Hawaii the least at 0.

Applied ML Scientist - Active Learning

Columbus, OH • On-site

Hexion
Chemical Manufacturing • 10K+ employees
Learn more about Hexionexternal

Other

Re-posted 20 days ago

Hexion rating

7.0

Company rating: 7.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

Job Responsibilities
  • Lead the design and execution of optimization and active-learning campaigns across chemistry, formulation, and process development.
  • Collaborate with R&D and manufacturing on framing optimization problems with design spaces, decision variables, objectives, and hard and soft constraints.
  • Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints.
  • Select and maintain surrogate models for acquisition, using model uncertainty to drive the search and respecting each model's domain of validity.
  • Drive closed-loop optimization that connects surrogate models to experimentation, with emphasis on decision quality, exploration versus exploitation, and actionable recommendations.
  • Partner with ML engineers, software engineers, and process engineers to deploy and monitor optimization systems.
  • Explore and adopt emerging ML methods, including LLM and agentic approaches, to advance optimization.
  • Communicate methods, results, and their limitations clearly to technical and non-technical audiences.
Minimum Qualifications
  • Bachelor's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field, with substantial relevant experience in ML modeling or optimization experience for chemistry, formulation, process, or manufacturing problems.
  • 7+ years experience.
  • Demonstrated expertise in Bayesian optimization and Gaussian processes, including kernels, acquisition functions, and batch, multi-objective, and constrained settings.
  • Experience designing and running experiment campaigns or closed-loop optimization.
  • Experience in applied statistics and uncertainty quantification, with emphasis on calibrated posteriors that drive acquisition.
  • Strong Python skills and experience with mainstream Python-based ML and Bayesian optimization frameworks and tools.
  • Active use of AI-assisted coding and other AI tools in daily work, with familiarity with emerging ML methods including LLM and agentic approaches.
  • Strong communication, collaboration, and stakeholder management skills for working with R&D, manufacturing, and business teams.
Preferred Qualifications
  • Master's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field.
  • Experience with active learning and physics-informed approaches for optimization in chemical synthesis, formulation, or process development.
  • Experience working with manufacturing, process, quality, or plant data, including issues such as batch-to-batch variability, raw-material variability, model drift, and changing operating conditions.
  • Familiar with ML engineering core tasks and techniques, such as data and optimization pipelines, model deployment, and MLOps.
  • Knowledge of chemistry ML core areas such as cheminformatics, molecular representation, predictive modeling, and chemistry foundation models.
Equal Opportunity Statement

We are an Equal Opportunity, Affi­ndant Anti­Ass­istant employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.

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