Postdoctoral Fellow in Industrial & Systems Engineering

The University of North Carolina; Town of Texas (WI); On-site; USD 40,000 - 65,000; Part time

Job summary

The University of North Carolina is seeking a Postdoctoral Fellow in Industrial & Systems Engineering based in the Town of Texas, Wisconsin. The Fellow will conduct advanced research in deep learning, focusing on developing novel algorithms and applying them to complex real-world problems. Applicants must hold a recent Ph.D. and have a strong background in optimization and machine learning. The role includes publishing research, supervising graduate students, and supporting ongoing research initiatives. This position promotes diversity and inclusivity in academia.

Qualifications

• Ph.D. must have been awarded within the last eight years.
• Strong experimental and theoretical background in relevant disciplines.
• Experience with large-scale optimization or deep learning systems is desirable.

Responsibilities

• Conduct advanced research in deep learning and optimization design.
• Develop novel algorithms and improve model efficiency.
• Contribute to scholarly publications and mentor graduate students.

Skills

Deep learning

Convex optimization

Machine learning

Stochastic gradient descent

Education

Ph.D. in Industrial Engineering or related field

Job description

Postdoctoral Fellow in Industrial & Systems Engineering

Position 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

Employment Type: Temporary - Part-time

Hours per Week: 40

Work Schedule: Varies

Pay Rate: Pay Rate varies

The Postdoctoral appointee must have recently (within the last eight years) been awarded a Ph.D.

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, focusing on optimization design and 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.

In this role, the Fellow will contribute to scholarly publications, support ongoing research initiatives with the supervisor, and serve as a research instructor to graduate students as the faculty mentor expands the research instruction function.

As an EOE/AA employer and an ADVANCE Institution that strives to create an inclusive academic climate, this position encourages applications from all underrepresented groups. Applicants are subject to a 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.