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Bayesian Phd Jobs in Idaho (NOW HIRING)

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.

What are popular job titles related to Bayesian Phd jobs in Idaho?

For Bayesian Phd jobs in Idaho, the most frequently searched job titles are:

What cities in Idaho are hiring for Bayesian Phd jobs?

Cities in Idaho with the most Bayesian Phd job openings:

AI-Enabled Catalyst Discovery Postdoctoral Researcher

Idaho Falls, ID • On-site


Idaho National Laboratory
Scientific Research and Development Services • 5 - 10K employees

8.8

Company rating: 8.8 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

16th of 120 rated laboratories

Great coworkers

People enjoy working here

Good employer


$105K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 3 days ago


Job description


Idaho National Laboratory is hiring a postdoctoral researcher in Chemical Engineering, Materials Science, Computer Science, Data Science, Applied Mathematics or closely related field to support our Integrated Energy Technologies Department. The postdoctoral researcher will lead the development of an artificial intelligence (AI)-enabled catalyst discovery workflow that integrates experimental data, mechanistic understanding, and machine learning to accelerate heterogeneous catalyst development for propane dehydrogenation. This position lies at the interface of catalysis, data science, and scientific software development, supporting the creation of a closed loop experimental and computational platform for autonomous catalyst optimization.
Our team works a 9x80 schedule located out of our Idaho Falls facility with every other Friday off.
Primary Responsibilities Include:
  • Design, develop, and maintain machine learning workflows for catalyst performance prediction and inverse catalyst design.
  • Develop forward predictive models that relate catalyst synthesis parameters, physiochemical characterization, and transient kinetic descriptors to catalytic performance metrics including yield, selectivity, and stability.
  • Implement inverse-design algorithms that recommend new catalyst compositions and synthesis conditions for experimental validation.
  • Integrate heterogeneous datasets generated from high-throughput synthesis, catalyst screening, transient kinetic measurements, and reactor scale testing into a unified data pipeline.
  • Develop automated data preprocessing, feature engineering, uncertainty quantification, model validation, and candidate-ranking workflows.
  • Interface machine learning models with the project's graph-based ontology and FAIR data infrastructure to enable automated model training and data ingestion.
  • Collaborate closely with catalyst synthesis, high-throughput screening, transient kinetics, and reactor testing teams to incorporate newly generated experimental data into iterative model refinement.
  • Evaluate model performance using statistical cross-validation and experimental validation across catalyst development scales, from research powders through technical catalyst forms.
  • Develop reproducible software, documentation, and visualization tools that support workflow deployment and long-term maintainability.
  • Contribute to publications, technical reports, software releases, presentations, and project reviews.

Required:
  • PhD in Chemical Engineering, Material Science, Computer Science, Data Science, Applied Mathematics, or a closely related field.
  • PhD requirements must be completed by commencement of appointment and within the previous 5 years.
  • Experience developing machine learning models using Python and scientific computing libraries (e.g., PyTorch, TensorFlow, scikit-learn).
  • Experience with scientific data analysis, statistical learning, and predictive modeling.
  • Strong programming skills and experience with software version control.
  • Demonstrated ability to work in multidisciplinary research teams.

The ideal candidate will possess:
  • Experience applying machine learning to chemistry, catalysis, material science, or reaction engineering.
  • Familiarity with Bayesian optimization, active learning, inverse design, or uncertainty quantification.
  • Experience with graph databases, knowledge graphs, or ontology development.
  • Experience developing scientific workflows for automated or high-throughput experimentation.
  • Knowledge of heterogeneous catalysis, reaction kinetics, or catalyst characterization techniques.
  • Experience with cloud computing, workflow orchestration, or containerized software environments.

Physical Requirements:
While performing the duties of this classification, the employee is frequently required to stand, walk, sit, stoop, bend, and work in an office and laboratory environment. The job requires hand/finger dexterity to keyboard or type, handle materials, manipulate tools, and reach with hands and arms. The job requires operation of job-related equipment. The employee must occasionally lift and/or move up to 25 pounds without assistance. Sufficient visual acuity and hearing capacity to perform the essential functions and interact with the people is required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Job Information:
  • The pay for this position is $105,144.00 Annually. At Idaho National Laboratory compensation decisions are determined using factors such as education, relevant experience, and other credentials.

About Us
Benefits and Relocation
  • Medical, Dental, Vision, and Flexible Spending Accounts
  • 401(k) with a 4.2% employer contribution and up to 4.8% match (regular positions) or self-contribute access (postdoctoral positions)
  • Paid time off (personal leave)
  • Employee Education Program (tuition assistance for eligible positions)
  • Comprehensive Relocation Package
  • Benefit eligibility subject to multiple factors, including employment status and position classification.

At this time, BEA will not sponsor any H1-B visas obtained outside of the United States of America (U.S.A.), including consular visas.
INL is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research, science, and national defense. With more than 6,300 scientists, researchers, and support staff, the laboratory works with national and international governments, universities and industry partners to change the world's energy future and secure our nation's critical infrastructure.
INL Mission:
Our mission is to discover, demonstrate and secure innovative nuclear energy solutions, other clean energy options and critical infrastructure.
INL Vision:
Our vision is to change the world's energy future and secure our nation's critical infrastructure.
Selective Service Requirements:
To be eligible for employment at INL males born after December 31, 1959 must have registered with the Selective Service System (SSS). For more information see www.sss.gov.
Equal Employment Opportunity:
Idaho National Laboratory (INL) is an Equal Employment Opportunity (EEO) employer. It is the policy of INL to provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
Reasonable Accommodation:
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Other Information:
When applying to positions please provide a resume and answer all questions on the following screens. Applicants, who fail to provide a resume or answer the questions, may be deemed ineligible for consideration.
INL does not accept resumes from third party vendors unsolicited.

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About Idaho National Laboratory

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Idaho National Laboratory is a leading multi-disciplinary national laboratory dedicated to supporting the U.S. Department of Energy's missions in nuclear and energy research, science, and national defence. Located in Idaho Falls, ID, US, it operates under the management of Battelle Energy Alliance. Since its inception in 1949, the lab has remained at the forefront of nuclear energy innovations and advancements, providing critical scientific and technological inputs to support national priorities. Guided by its commitment to excellence, innovative research, collaborative partnerships, and integrity, the lab continues to play a vital role in driving America's nuclear and energy future.

Industry

Scientific research and development services

Company size

5,001 - 10,000 Employees

Headquarters location

Idaho Falls, ID, US

Year founded

1949

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Benefits

Hours and flexibility

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