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Postdoctoral Fellow Machine Learning Jobs in Virginia

$64K - $76K/yr

LEARNING OBJECTIVES The postdoctoral fellow will have the opportunity to perform various projects through wet laboratory benchwork. The knowledge gained will allow them to contribute to seminars ...

$64K - $76K/yr

LEARNING OBJECTIVES The postdoctoral fellow will have the opportunity to perform various projects through wet laboratory benchwork. The knowledge gained will allow them to contribute to seminars ...

$64K - $76K/yr

LEARNING OBJECTIVES The postdoctoral fellow will have the opportunity to perform various projects through wet laboratory benchwork. The knowledge gained will allow them to contribute to seminars ...

The postdoctoral fellow will work under the supervision of Prof. Yingda Cheng on computational ... Experience with writing scientific machine learning. Overtime Status Exempt: Not eligible for ...

Postdoctoral Associate Apply now Back to search results Job no: 536282 Work type: Research Faculty ... AI for cybersecurity, including the use of machine learning and large language models for cyber ...

... datasets and machine learning approaches to identify FDA approved drugs that target key ... The candidate, one of six new postdoctoral fellows to be hired within the newly NSF-funded COMPASS ...

Postdoctoral Associate Apply now Back to search results Job no: 534769 Work type: Research Faculty ... and machine learning. The position will start in fall 2026 and will be for two years, with a ...

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Postdoctoral Fellow Machine Learning information

What are the key skills and qualifications needed to thrive as a Postdoctoral Fellow in Machine Learning, and why are they important?

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 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 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 Virginia? For Postdoctoral Fellow Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Postdoctoral Fellow Machine Learning jobs in Virginia look for? The top searched job categories for Postdoctoral Fellow Machine Learning jobs in Virginia are:
Postdoctoral Associate

Full-time

Posted 8 days ago


Virginia Tech rating

7.7

Company rating: 7.7 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

211th of 530 rated colleges and universities


Job description

Postdoctoral Associate
Job no: 534113
Work type: Research Faculty
Senior management: College of Science
Department: Mathematics
Location: Blacksburg, Virginia
Categories: Instructional / Teaching Faculty, Research / Scientific
Job Description
Applications are invited for one Postdoctoral Associate position with the Department of
Mathematics at Virginia Tech, Blacksburg, VA. The postdoctoral fellow will work under the supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order models and machine learning techniques for kinetic equations arising from plasma and neutron transport.
The position will be based at Virginia Tech's campus in Blacksburg, VA. The postdoc will have a teaching load of 2 classes per year. The position is for two years, and can be renewed for a third year pending satisfactory performance.
Required Qualifications
• A PhD in Mathematics or an equivalent area, and with a strong background in numerical analysis and scientific computing. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Strong background in the development and/or application of numerical methods for partial differential equations.
• Experience in implementation of numerical methods.
• Interest and experience in at least one application from the areas mentioned above.
• Ability to work with others in an interdisciplinary environment.
Preferred Qualifications
• Experience with the scientific computing library and parallel programming.
• Experience with writing scientific articles.
• Experience with writing scientific machine learning.
Overtime Status
Exempt: Not eligible for overtime
Appointment Type
Restricted
Salary Information
Commensurate with experience
Hours per week
40 hours - exempt position
Review Date
December 1, 2025
Additional Information
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.
Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.
If you are an individual with a disability and desire an accommodation, please contact Sarah McDearis at sworl9@vt.edu during regular business hours at least 10 business days prior to the event.
Advertised: February 23, 2026
Applications close:
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About Virginia Tech

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Virginia Tech, guided by its motto "Ut Prosim" (That I May Serve), embraces a hands-on, interdisciplinary approach to educate scholars as leaders and problem-solvers. As a comprehensive land-grant institution, it enriches the quality of life in Virginia and worldwide, fostering an inclusive community focused on knowledge, discovery, and creativity. With over 280 majors, the university serves a diverse student body of more than 36,000 across undergraduate, graduate, and professional programs. Virginia Tech's presence extends throughout Virginia, including campuses in Northern Virginia, Roanoke, Newport News, and Richmond, along with multiple Extension offices and research centers. As a prominent global research institution, it conducts over $500 million in research annually.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Blacksburg, VA, US

Year founded

1872

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