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Post Doc Research Scholar (Post Doc)

North Carolina State University
$65,000
relocation assistance
United States, North Carolina, Raleigh
Nov 08, 2024
Position Information


Posting Number PG191326PD
Position Number 00111051
Position Type Post Doc
FLSA Exempt
Departmental Information


Department ID 140601 - Fitts Department of Industrial & Systems Engineering
Department 140601 - Fitts Dept Indust & Syst Engr
Job City & State Raleigh, NC
Position Overview


Essential Job Duties
Professor Shashaani needs a postdoctoral research scholar to assist with ongoing research on stochastic derivative-free optimization. Duties and responsibilities include:

  • Design and analysis of algorithms for nonlinear optimization algorithms that use noisy simulation outputs to handle high-dimensionality, constraints, and nonsmoothness
  • Implementation of developed algorithms in code using Python and Julie, version control and documentation with GitHub
  • Analysis of computational experiments to evaluate algorithm performance with different testbeds using high-performance computing
  • Preparing manuscripts for publication and reports and other proposals for the funding agencies
  • Presenting findings at relevant conferences or seminars


Other Duties and Responsibilities

  • Execution and analysis of computational experiments to evaluate performance using high-performance computing
  • Preparing manuscripts for publication
  • Presenting findings at relevant conferences

Up to $5,000 relocation assistance and $3,000 travel support for national and international conferences.
Other Work/Responsibilities

  • Assistance with mentoring PhD students in the research group or with teaching tasks
  • Participation in developing proposals for outside research funding

Requirements and Preferences


Work Schedule 8:00am - 5:00pm Monday-Friday (hybrid)
Department Required Skills

  • Thorough understanding of optimization methodology for nonlinear optimization problems, particularly constrained optimization of nonconvex problems
  • Thorough familiarity with probability theory and analysis of stochastic processes
  • Thorough familiarity with implementing optimization algorithms using Python or Giulia and familiarity with GitHub platforms
  • Strong oral and written communication skills
  • Experience developing, implementing and analyzing large-scale computational experiments


Preferred Years Experience, Skills, Training, Education
Ph.D or equivalent doctorate in Industrial and Systems Engineering or a related field,
no more than 2 years from receipt of application.
Required License or Certification
N/A
Valid NC Driver's License required? No
Commercial Driver's License Required? No
Recruitment Details


Anticipated Hiring Range $65,000
If you anticipate multiple hires from this search, please indicate how many
Recruitment Dates


Job Open Date 09/09/2024
Applicant Information


Quick Link https://jobs.ncsu.edu/postings/207910
AA/EEO
NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran. Individuals with disabilities requiring disability-related accommodations in the application and interview process are welcome to contact 919-515-3148 to speak with a representative at the Office of Institutional Equity and Diversity.

If you have general questions about the application process, you may contact Human Resources at (919) 515-2135 or workatncstate@ncsu.edu.

Final candidates are subject to criminal & sex offender background checks. Some vacancies also require credit or motor vehicle checks. Degree(s) must be obtained prior to start date in order to meet qualifications and receive credit.

NC State University participates in E-Verify. Federal law requires all employers to verify the identity and employment eligibility of all persons hired to work in the United States.
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