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Postdoctoral Fellow Machine Learning Jobs in Pittsburgh, PA

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Postdoctoral Fellow Machine Learning information

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$24.3K

$57.3K

$81.1K

How much do postdoctoral fellow machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for postdoctoral fellow machine learning in Pittsburgh, PA is $57,299.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,600.00 and $64,600.00 per year, depending on experience, location, and employer.

What is a postdoctoral fellow in machine learning?

A Postdoctoral Fellow in Machine Learning is a researcher who has recently completed their PhD and is engaged in advanced research in the field of machine learning. This role typically involves conducting independent or collaborative research, publishing scientific papers, and sometimes mentoring students. Postdoctoral fellows often work at universities, research institutes, or industry labs, focusing on developing new algorithms, improving existing models, or applying machine learning techniques to specific problems. The position is usually temporary, lasting one to three years, and aims to prepare researchers for permanent academic or industry roles.

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

To thrive as a Postdoctoral Fellow in Machine Learning, you need a strong background in computer science, mathematics, and statistics, typically supported by a PhD and relevant research experience. Familiarity with programming languages such as Python, machine learning frameworks like TensorFlow or PyTorch, and experience in high-performance computing environments are commonly required. Strong analytical thinking, effective scientific communication, and collaboration skills help you contribute to research teams and disseminate findings. These skills and qualities are crucial for advancing research, developing innovative solutions, and building a successful academic or industry career in machine learning.

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

Postdoctoral Fellows in Machine Learning often encounter challenges such as balancing independent research with collaborative projects, staying current with rapidly evolving technologies, and securing funding or publishing in top-tier journals. To address these, it's helpful to establish clear communication with mentors and collaborators, set aside dedicated time for reading recent literature, and actively seek feedback on research drafts. Building a professional network through conferences and seminars can also open opportunities for collaboration and career advancement.

What is the difference between Postdoctoral Fellow Machine Learning vs Postdoctoral Research Scientist?

AspectPostdoctoral Fellow Machine LearningPostdoctoral Research Scientist
Required credentialsPhD in Computer Science, Data Science, or related fieldPhD in relevant field, often with specialized research experience
Work environmentAcademic labs, universities, research institutionsResearch labs, industry R&D departments, tech companies
Employer and industry usagePrimarily academia, government researchPrimarily industry, corporate research divisions
Common search and comparison intentUnderstanding academic research roles in machine learningExploring industry-focused research career paths

Postdoctoral Fellow Machine Learning roles typically focus on academic research, requiring a PhD and working in universities or research institutions. In contrast, Postdoctoral Research Scientist positions are often industry-based, emphasizing applied research within corporate R&D departments. Both roles involve advanced machine learning expertise but differ mainly in work environment and career trajectory.

What are popular job titles related to Postdoctoral Fellow Machine Learning jobs in Pittsburgh, PA?

For Postdoctoral Fellow Machine Learning jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching Postdoctoral Fellow Machine Learning jobs in Pittsburgh, PA look for?

The top searched job categories for Postdoctoral Fellow Machine Learning jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for Postdoctoral Fellow Machine Learning jobs?

Cities near Pittsburgh, PA with the most Postdoctoral Fellow Machine Learning job openings:

Postdoctoral Fellow Machine Learning jobs near you

Post Doctoral Associate - Sakurahara Lab

University of Pittsburgh

Pittsburgh, PA • On-site

$47K - $64K/yr

Full-time

Re-posted 20 days ago

Job description

The Risk Analysis and Reliability Engineering (RARE) Laboratory at the University of Pittsburgh's Swanson School of Engineering conducts research to advance probabilistic risk assessment (PRA) to enhance the safety, efficiency, and usability of nuclear energy systems. The lab develops advanced PRA methodologies integrating physics-based simulations, Bayesian inference, and AI/machine learning tools to support risk-informed decision-making for both existing nuclear fleets and advanced reactors. Current projects include PRA for advanced reactors, integrated energy systems risk analysis, and AI-driven safety analysis tools with broad applicability across high-consequence industries.

Required Educational Background:
PhD in nuclear engineering or a relevant field (mechanical engineering, industrial engineering, etc.) with a research focus on probabilistic risk assessment and reliability engineering of nuclear energy systems.

Required Skillset:
Familiarity with nuclear power plant systems and hands-on experience with PRA software (e.g., CAFTA, SAPHIRE, and OpenPSA). Proficiency in scientific programming (e.g., Python) and exposure to AI/ML methods are required. A strong track record of publications, teamwork, proposal writing support, and mentorship is expected. 

Responsibilities:
Conduct research advancing PRA methodologies through expanded integration of physics-based simulations and AI tools. Disseminate research results through peer-reviewed journal publications and conference presentations. Support the PI in mentoring graduate and undergraduate researchers. Contribute to the development of external grant proposals.

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