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Postdoctoral In Reinforcement Learning Jobs in Fort Mill, SC

Belk

Decision Scientist

Charlotte, NC · On-site

Support or contribute to reinforcement learning, multi-armed bandit, or contextual bandit frameworks as part of the NBA decisioning engine, with opportunity to grow expertise in this area * Develop ...

Bank of America

Data Scientist I

Charlotte, NC · On-site

Demonstrated prior experience through work, research or passion projects in RAG, Agentic Frameworks, LLMs, Reinforcement Learning * Are energized by the high stakes and intensity of dynamic ...

1 point system

GenAI Product Engineering Lead

Rock Hill, SC · On-site

$85K - $112K/yr

Expertise in Azure AI (including Foundry) and building agentic GenAI applications end-to-end ... Oversee model evaluation, tuning, and continuous improvement cycles using reinforcement learning ...

Varsity Tutors

BCABA Tutor

Charlotte, NC · Remote

$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 ...

Varsity Tutors

BCABA Tutor

Matthews, NC · Remote

$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 ...

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Postdoctoral In Reinforcement Learning information

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$22K

$51.9K

$73.4K

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

As of Sep 11, 2026, the average yearly pay for postdoctoral in reinforcement learning in Fort Mill, SC is $51,865.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,100.00 and $58,400.00 per year, depending on experience, location, and employer.

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.

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 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 job categories do people searching Postdoctoral In Reinforcement Learning jobs in Fort Mill, SC look for?

The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Fort Mill, SC are:

Postdoctoral In Reinforcement Learning jobs near you
Infographic showing various Postdoctoral In Reinforcement Learning job openings in Fort Mill, SC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $51,865 per year, or $24.9 per hour.

Postdoctoral Fellow in Industrial & Systems Engineering

Charlotte, NC • On-site

University of North Carolina at Charlotte
See more jobs at University of North Carolina at Charlotteexternal

$44K - $60K/yr

Full-time, Part-time

Re-posted 25 days ago

The University Of North Carolina At Charlotte rating

6.6

Company rating: 6.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job description

Position Information
General Information
Position Number
POST40
Working Title
Postdoctoral Fellow in Industrial & Systems Engineering
Division
Academic Affairs
Department
College of Engineering (Col)
Work Unit
Dept of Industrial & Systems Engin
Work Location
Smith
Vacancy Open To
All Candidates
Position Designation
Post Doc
Employment Type
Temporary - Part-time
Hours per week
40
Work Schedule
Varies
Pay Rate
Pay Rate varies
Minimum Experience/Education
The Postdoctoral appointee must have recently (within the last eight years) been awarded a Ph.D.
Departmental Preferred Experience, Skills, Training/Education:
  • Ph.D. in Industrial Engineering, Operations Research, Industrial and Systems Engineering, Computer Science, or a closely related quantitative discipline
  • A strong experimental and theoretical background with evidence of both skills related to convex optimization, machine learning, stochastic gradient descent, and deep learning
  • Demonstrated experience in developing, analyzing, and implementing optimization algorithms and/or machine learning models for complex systems or real-world applications
  • Experience with large-scale optimization or deep learning systems is highly desirable

Duties and Responsibilities
The Postdoctoral Fellow will conduct advanced research in deep learning, with a focus on optimization design and/or the application of deep learning methods to complex real-world problems. The position aims to develop novel algorithms, improve model efficiency and performance, and translate theoretical advances into practical solutions across relevant domains. The Fellow will contribute to scholarly publications, and support ongoing research initiatives with the supervisor.
A Postdoctoral Fellow (""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop further the research skills acquired in their doctoral programs or to learn new research techniques, in preparation for an academic or research career. In the process of further developing their own research skills, it is expected that Postdoctoral Fellows will also play a significant role in the performance of research at the University and augment the role of graduate faculty in providing research instruction to graduate students. A Postdoctoral Fellow works under the supervision of a regular faculty member, who serves as a mentor to the Fellow, and it is expected that the faculty mentor will impart the realities, and variety, of scientific careers, and will encourage experiences outside the laboratory to broaden postdocs' aspirations. Within the confines of the particular research focus assigned by that faculty member, the Postdoctoral Fellow functions with a considerable degree of independence and has the freedom (and is expected) to publish the results of his or her research or scholarship during the period of appointment. Thus, the role of Postdoctoral Fellows is clearly differentiated from full-time technical employees.
Postdoc appointments are characterized by all the following conditions:
* the appointee was recently (within the last eight years) awarded a Ph.D.
* the appointment is temporary;
* the appointment involves substantially full-time research or scholarship;
* the appointment is viewed as preparatory for a full-time academic and/or research career;
* the appointee works under the supervision of a faculty member; and
* the appointee has the freedom and is expected to publish the results of his or her research or scholarship during the period of appointment.
As an EOE/AA employer and an ADVANCE Institution that strives to create an academic climate in which the dignity of all individuals is respected and maintained, the University of North Carolina at Charlotte encourages applications from all underrepresented groups. Applicants subject to criminal background check.
Other Work/Responsibilities
The Postdoctoral Fellow is expected to exercise a high degree of independent judgment in the design, execution, and interpretation of research activities. The Fellow will be responsible for selecting appropriate methodological approaches in deep learning and optimization, formulating research problems, and determining suitable experimental and analytical strategies.
Necessary Licenses or Certifications
Proposed Hire Date
06/01/2026
Contact Information
Expected Length of Assignment
One year
Posting Open Date
04/20/2026
Posting Close Date
Special Notes to Applicants
Please upload the following documents with your electronic submission:
1. Cover letter
2. Curriculum Vitae.
4. Contact information for three references
Finalists will be required to complete a criminal background check and
submit their official transcripts.

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