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Postdoctoral In Reinforcement Learning Jobs in Minneapolis, MN

University of Minnesota

Faculty Positions

Minneapolis, MN · On-site

$110K - $130K/yr

... in artificial intelligence and machine learning. Theoretical areas of interest include (but are not limited to) optimization, neural networks, and reinforcement learning. Application areas of ...

Big Lake Public Schools #727

Paraeducator

Big Lake, MN · On-site

Working under the direct supervision of licensed instructional personnel, positions in this classification provide reinforcement to students individually or in small groups to support their learning ...

Big Lake Public Schools #727

Paraeducator

Big Lake, MN · On-site

Working under the direct supervision of licensed instructional personnel, positions in this classification provide reinforcement to students individually or in small groups to support their learning ...

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Postdoctoral In Reinforcement Learning information

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$26.1K

$61.6K

$87.2K

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

As of Aug 21, 2026, the average yearly pay for postdoctoral in reinforcement learning in Minneapolis, MN is $61,607.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,100.00 and $69,400.00 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 are popular job titles related to Postdoctoral In Reinforcement Learning jobs in Minneapolis, MN?

For Postdoctoral In Reinforcement Learning jobs in Minneapolis, MN, the most frequently searched job titles are:

What job categories do people searching Postdoctoral In Reinforcement Learning jobs in Minneapolis, MN look for?

The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Minneapolis, MN are:

What cities near Minneapolis, MN are hiring for Postdoctoral In Reinforcement Learning jobs?

Cities near Minneapolis, MN with the most Postdoctoral In Reinforcement Learning job openings:

Postdoctoral In Reinforcement Learning jobs near you

Senior AI/ Data Scientist - Pricing & Promotion

Cargill

Wayzata, MN • On-site

$105K - $160K/yr

Full-time

Re-posted 26 days ago

Cargill rating

7.4

Company rating: 7.4 out of 10

Based on 224 frontline employees who took The Breakroom Quiz

20th of 49 rated food wholesalers

Job description

Cargill is a family company committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. We sit at the heart of the supply chain, partnering with producers and customers to source, make and deliver products that are vital for living. By providing customers with life's essentials, we enable businesses to grow, communities to prosper, and consumers to live well.
This position is in our Food Enterprise where we are committed to serving food manufacturers, food service customers, and retailers with a complete range of innovative ingredients and branded products. Our portfolio includes poultry, beef, egg, alternative protein, salt, oils, starches, sweeteners, cocoa and chocolate.
Job Purpose and Impact
The Senior AI & Data Science job plans and leads the development of artificial intelligence models from design and prototyping through deployed solutions to drive decision making. With minimal supervision, this role extracts and integrates complex data from various sources, builds advanced models suitable for the business use case and evaluates model performance for accuracy, scaling and deployment. This job also develops compelling and clear communication materials to facilitate partner on board. By leveraging diverse and expansive data sources, this role applies advanced forecasting, optimization, and machine learning techniques to transform how decisions are made across the supply chain. The Senior Professional accelerates AI adoption by partnering with business and technology teams. They work to embed models into core workflows, operationalizing data science to deliver sustained business impact.
Key Accountabilities
  • DATA PREPARATION MANAGEMENT: Conducts extraction and integration of complex data from different data sources, analyses the ways in which datasets may be biased and applies mitigation strategies.
  • DATA ANALYSIS: Reviews complex data sets for exploratory data analysis to identify trends and patterns that inform business strategies across various areas.
  • MODEL DEVELOPMENT: Develops and deploys artificial intelligence models, including monitoring and evaluating ongoing performance to solve complex business problems and derive actionable insights.
  • AI ENGINEERING: Establishes software and artificial intelligence engineering patterns and principles to design, develop, test, integrate, maintain and troubleshoot complex and varied generative artificial intelligence software solutions and incorporates security practices in newly developed and maintained applications. .
  • DOCUMENT & REPORTING: Documents development and code in ways that allow for support and knowledge sharing.
  • COMMUNICATION: Presents techniques and results to technical and non-technical audiences.
  • CONTINUOUS LEARNING: Examines existing and emerging artificial intelligence and optimization principles, theories, and techniques to develop and deploy artificial intelligence models into production, improving the organization's analytical capabilities.
  • STAKEHOLDER MANAGEMENT: Works closely with businesses to understand needs, and collaborates with cross functional teams to develop artificial intelligence models for digital applications.

Qualifications
  • Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.

Preferred Qualifications:
  • Master's degree or PhD in Applied Mathematics, Computer Science, Data Science, Operations Research, or a related field.
  • Deep experience leading the design, deployment, and scaling of applied AI/ML solutions that drive measurable business impact across complex value chains.
  • Advanced expertise in Machine Learning, Deep Learning, and/or Reinforcement Learning, including model governance, performance monitoring, and lifecycle ownership.
  • Recognized depth in forecasting and optimization, with a track record of influencing enterprise-level decisions in pricing & commercial.

#HiPo
This role is not eligible for employer-sponsored work authorization now or in the future. This includes candidates whose work authorization is tied to a student visa, employer-sponsored visa, visa transfer, immigration petition, or other third-party sponsorship arrangement.
Short Description
The expected salary for this position is $105,000 - $160,000. Compensation varies depending on a wide array of factors including but not limited to the specific location, certifications, education, and level of experience. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled. This position is eligible for a discretionary incentive award. The incentive award amount is dependent upon company performance and your personal performance. At Cargill we put people first. As part of your overall rewards, we offer a comprehensive benefit program including medical and/or other benefits dependent on the position offered and hours worked. Visit: https://www.cargill.com/page/my-health/mh-health-and-wellness to learn more (subject to certain collective bargaining agreements for Union positions).
Minnesota Sick and Safe Leave accruals of one hour for every 30 worked, up to 48 hours per calendar year unless otherwise provided by law.
Equal Opportunity Employer, including Disability/Vet

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About Cargill

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Cargill was founded in 1865 as a single grain warehouse in Iowa, U.S. Since then, we’ve grown to become a global partner connecting people around the planet. But one thing has remained constant over the years: our purpose of nourishing the world in a safe, responsible and sustainable way. Cargill is committed to conducting business with integrity, operating responsibly, enriching communities and nourishing the world. In the fiscal year 2021, Cargill provided $110.5 million in total charitable contributions in 56 countries to support our communities. Cargill businesses and employee-led groups partner with local civic, nonprofit and non-governmental organizations on programs and projects that improve food security and nutrition; support human rights, equity and inclusion; strengthen farmer livelihoods; and advance our commitments in the areas of land use, water and climate.

Industry

Food and drink manufacturing

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

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