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Postdoctoral In Reinforcement Learning Jobs in Arnold, MO

BCABA Tutor

Saint Louis, MO ยท Remote

$18 - $40/hr

Ability to explain reinforcement schedules, functional behavior assessment, and behavior ... in learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring ...

Post Doctoral Fellow

Saint Louis, MO ยท On-site

$47K - $64K/yr

... Postdoctoral Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data ... Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival ...

Post Doctoral Fellow

Saint Louis, MO ยท On-site

$47K - $64K/yr

... highly motivated Postdoctoral Fellowwith a PhD in Computational Biology, Bioinformatics ... Develop and apply statistical and machine-learning models(e.g., mixed-effects models, survival ...

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Postdoctoral In Reinforcement Learning information

See Arnold, MO salary details

$22.1K

$52.3K

$73.9K

How much do postdoctoral in reinforcement learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for postdoctoral in reinforcement learning in Arnold, MO is $52,269.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,400.00 and $58,900.00 per year, depending on experience, location, and employer.

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

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

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

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

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a postdoctoral researcher in reinforcement learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
Infographic showing various Postdoctoral In Reinforcement Learning job openings in Arnold, MO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $52,269 per year, or $25.1 per hour.

Postdoctoral Research Associate - Oncology

Washington University

Saint Louis, MO โ€ข On-site

Full-time

Re-posted yesterday


Job description

Location
ST. LOUIS, MO 63110Position Summary
This posting is for a Postdoctoral Research Associate position in Dr. David Spencer's Lab in the Division of Oncology, Department of Medicine.
Dr. David Spencer is seeking a postdoctoral researcher to lead exciting new projects in the field of Cancer Genetics. The Spencer lab studies human genomics, cancer genetics, gene regulation, and the genomics and epigenetics of acute myeloid leukemia and has published articles in Cancer Cell, Cell, Leukemia, and the New England Journal of Medicine. The lab has extensive expertise in both bench science and bioinformatics and is a key member of the cancer genetics group at WashU and Siteman Cancer Center. Dr. Spencer has received funding from ASH, the Cancer Research Foundation, Doris Duke, Siteman Cancer Research Fund, and the NCI, and has extensive collaborations with the McDonnell Genome Institute.
Position will play a lead role in new studies of epigenetics, DNA methylation, and gene regulation in acute myeloid leukemia using primary human samples, cell lines, and mouse models. Responsibilities will be to design, perform, and analyze data from genomic assays including long read sequencing using the Oxford Nanopore and Pacific Biosciences platforms, single-cell multi-omics, 3D genome architecture studies (e.g., Micro-C and HiC), CUT&RUN and CUT&Tag. Experimental systems will include CRISPR/Cas9-mediated genetic and epigenetic manipulation of AML cells and massively parallel reporter assays to investigate gene regulation in leukemia. Computational analysis of these data will involve applying existing tools and developing new ones, including machine and deep learning methods. There will be opportunities for development of new cell line and animal models and testing, evaluation, and analysis of new genomic technologies. Authorship on high-profile publications resulting from this work is expected.
The postdoc will work directly with Dr. Spencer on a day-to-day basis, allowing for close mentorship to promote career development, including an independent research program and external funding. Further career and professional development training provided through the Career Center, Teaching Center, Office of Postdoctoral Affairs, and campus groups.
Job Description
Primary Duties & Responsibilities:
Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/.
Trains under the supervision of a faculty mentor including (but not limited to):
  • Assists with grant preparation and reporting.
  • Prepares and submits papers on research.
  • Assists in the design of research experiments.
  • Evaluates research findings and assists in the reporting of the results.
  • Conscientious discharge of their research responsibilities.
  • Maintains conformity with ethical standards in research.
  • Maintains compliance with good laboratory practice including the maintenance of adequate research records.
  • Engages in open and timely discussion with their mentor regarding possession or distribution of material, reagents, or records belonging to their laboratory and any proposed disclosure of findings or techniques privately or in publications.
  • Collegial conduct towards co-trainees, staff members and members of the research group.
  • Adherence to all applicable University policies, procedures and regulations. All data, research records and materials and other intellectual property generated in University laboratories remain the property of the University.

Working Conditions:
This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals.
Salary Range:
Base pay is commensurate with experience.
The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.
Required Qualifications
Education:
Ph.D., M.D. Or Equivalent Terminal Or Doctoral Degree.
Certifications/Professional Licenses:
No specific certification/professional license is required for this position.
Work Experience:
No specific work experience is required for this position.
Skills:
Not Applicable
Driver's License:
A driver's license is not required for this position.
More About This Job
At WashU, postdoctoral appointments:
  • Have a 5-year term limit that includes previous experience.

Preferred Qualifications
Education:
No additional education unless stated elsewhere in the job posting.
Certifications/Professional Licenses:
No additional certification/professional licenses unless stated elsewhere in the job posting.
Work Experience:
No additional work experience unless stated elsewhere in the job posting.
Skills:
Cell Cloning, Cell Culture Work, Cellular Biology Techniques, ChIP-Seq, Collaboration, CRISPR-Cas System, Data Analysis, Data Interpretations, Data Management, Experimentation, Laboratory Operations, Laboratory Techniques, Molecular Biology Techniques, PCR Methods, Researching, Results Reporting, RNA-Seq, Scientific Writing, Statistical Analysis, Unix Commands
Questions
For frequently asked questions about the application process, please refer to our External Applicant FAQ.
Accommodation
If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request.
All qualified individuals must be able to perform the essential functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential functions of their job, absent undue hardship.
Pre-Employment Screening
All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.
Benefits Statement
Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits.
EEO Statement
Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University's policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information.