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Postdoctoral In Reinforcement Learning Jobs in Minnesota

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 ...

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Postdoctoral In Reinforcement Learning information

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.

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Postdoctoral In Reinforcement Learning jobs near you

Sr. Director, AI & Data Science

Veracity Software Pvt. Ltd.

Wayzata, MN • On-site

Full-time

Re-posted 12 days ago

Job description

Job Summary:
Veracity Software Pvt. Ltd. is seeking a visionary leader for the role of Sr. Director, AI & Data Science. This role is responsible for uncovering and enabling high-impact applications of artificial intelligence across the business, partnering with leaders to identify innovative opportunities and ensuring responsible AI practices are embedded in every initiative.
Responsibilities:
• Partners with business leaders to identify and accelerate AI opportunities through re-imagining how work is performed, embracing new and modern optimization techniques and changing the pace by which business value is realized.
• Translates complex AI capabilities into compelling business narratives, presenting to and influencing non-technical audiences and senior stakeholders to drive informed strategic decisions and foster confidence in AI-driven innovation.
• Provides strategic direction of product delivery to ensure scope, timeline and budget are prioritized and in compliance with related regulations and policies.
• Leads all aspects of ongoing efforts to guide and improve artificial intelligence and data science design & development practices, champions a culture of innovation and continuous improvement within the organization and partners with key team members to drive artificial intelligence literacy and adoption.
• Develops and sponsors a community of practice of global data scientists to drive reuse, awareness and alignment to further the company's adoption and value through analytics solutions.
• Presents and sells artificial intelligence solutions to non-technical audiences to influence strategic related decisions.
• Accountable for delivering measurable business outcomes from artificial intelligence investments, with responsibility for handling a significant budget and achieving defined value impact targets.
• Builds strategic partnerships and alliances with key business and industry entities to achieve organizational objectives and improve the value of investments.
• Manages team members to achieve organization goals, provides technical coaching & guidance, drives accountability for high performance and develops and sustains an environment for data scientists to thrive in an inclusive culture.
• Other duties as assigned.
Qualifications:
Required:
• Bachelor's degree in data science, computer science, math, engineering or related field or equivalent experience
• Minimum of eight years of related work experience
• Experience in a minimum of two machine learning algorithms approaches: unsupervised, supervised and reinforcement learning
• Confirmed ability to present to non-technical audiences
Preferred:
• Master's degree or PhD in data science, computer science, math, engineering or related field
• Five years of experience leading teams
• Experience driving analytics adoption and mobilizing business transformation through AI adoption
• Broad expertise of business processes and functions
• Proficient in communicating to senior executives on opportunity and value, relating to the audience at hand
• Experience working with continuous integration and delivery (CI/CD) pipelines
• Experience working with distributed computing frameworks
• Experience working with AWS
• Experience in software development environment and code management or versioning
• Experience in agriculture
Company:
At Veracity, if you have an idea you want to validate, a product you need to build, or an existing product that needs optimization, our teams are trained to jump in wherever needed. Founded in 2010, the company is headquartered in Iselin, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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