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Postdoctoral In Bayesian Statistics Jobs in Ohio

Ohio State University

Postdoctoral Scholar

Columbus, OH

$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 ...

Varsity Tutors

Statistics Graduate Level Tutor

Akron, OH · Remote

$18 - $40/hr

... In a Statistics Graduate Level Tutor * Advanced Subject Mastery: Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian ...

Ohio State University

Postdoctoral Scholar

Columbus, OH

$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 ...

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Postdoctoral In Bayesian Statistics information

What is a postdoctoral position in Bayesian statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in Bayesian statistics?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

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For Postdoctoral In Bayesian Statistics jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Postdoctoral In Bayesian Statistics jobs in Ohio look for?

The top searched job categories for Postdoctoral In Bayesian Statistics jobs in Ohio are:

What cities in Ohio are hiring for Postdoctoral In Bayesian Statistics jobs?

Cities in Ohio with the most Postdoctoral In Bayesian Statistics job openings:

Postdoctoral In Bayesian Statistics jobs near you
Infographic showing various Postdoctoral In Bayesian Statistics job openings in Ohio as of August 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Applied ML Scientist - Active Learning

Hexion Inc.

Columbus, OH • On-site

Full-time

Re-posted 29 days ago

Hexion rating

7.0

Company rating: 7.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

74th of 100 rated chemical manufacturers

Job description

Job Summary:
Hexion Inc. is a company that pushes boundaries and creates impactful solutions through science. They are seeking an Applied ML Scientist to lead optimization and active-learning campaigns, collaborating with R&D and manufacturing to enhance processes and drive innovation.
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.
Qualifications:
Required:
• 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:
• 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.
Company:
Based in Columbus, Ohio, Hexion Inc. is a leading global producer of adhesives and performance materials. Founded in 1989, the company is headquartered in Mount Maunganui, NZL, with a team of 1001-5000 employees. The company is currently Late Stage.

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