Position Function:
An NSF-funded postdoc position is available in the lab of Megan Smith in the Department of Biological Sciences at Mississippi State University. The project aims to develop robust, user-friendly machine learning tools for population genetic inference and to apply these tools to uncover the drivers of diversification in several empirical systems. The lab has developed a Python package for demographic inference using machine learning, and the successful candidate will extend these methods along several axes.
In addition to the current project, the lab is pursuing a wide range of empirical and computational research in phylogenetics and population genetics. To learn more about our work visit https://www.meganlsmith.org
Salary Grade : UC
For salary grade UC, these positions are "Unclassified" and salary ranges are determined by the hiring department.
Department Profile:
The Department of Biological Sciences at MSU is home to a large, active group in evolutionary biology. Mississippi State University is a comprehensive Carnegie R1 “Very High Research Activity” campus and a top-100 university by research expenditure. The campus is situated in a small, inclusive community boasting a high standard of living (https://starkville.org). Within a short drive of Starkville are more than 120,000 acres of state and federal natural areas, with abundant opportunities for research and recreation. This includes the Sam D. Hamilton Noxubee National Wildlife Refuge (https://www.fws.gov/refuge/sam-d-hamilton-noxubee), and the Tombigbee National Forest.
Anticipated Appointment Date:
October 1, 2026 or thereafter
Tenure Track Status:
N/A
Essential Duties and Responsibilities:
The successful applicant will, amongst other research tasks:
- Develop and optimize popai, a Python package for population genetic inference using machine learning;
- Implement efficient pipelines on HPC systems;
- Mentor undergraduates and graduate students; and
- Lead and contribute to manuscripts, documentation, and workshops.
Minimum Qualifications:
PhD in a related field at the time of appointment, and a record of scholarly publication.
Preferred Qualifications:
Experience in population genetics or phylogenetics is preferred.
Knowledge, Skills, and Abilities:
Strong quantitative and programming skills, particularly in Python.
Strong written and verbal communication skills.
Demonstrated research productivity.
Working Conditions and Physical Effort
Typical office and professional environment.
Instructions for Applying:
To apply please submit (i) a full CV; (ii) a brief statement of research interests; and (iii) contact information for three references electronically to ms4438@msstate.edu. Applications will be reviewed on a rolling basis. The earliest possible start date for this position is October 1, 2026
Restricted Clause:
Position is contingent upon continued availability of funding.
Equal Employment Opportunity Statement:
Mississippi State University is an equal opportunity institution. Discrimination is prohibited in university employment, programs or activities based on race, color, ethnicity, sex, pregnancy, religion, national origin, disability, age, sexual orientation, genetic information, status as a U.S. veteran, or any other status to the extent protected by applicable law. Questions about equal opportunity programs or compliance should be directed to the Office of Civil Rights Compliance, 231 Famous Maroon Band Street, P.O. 6044, Mississippi State, MS 39762, (662) 325-5839.
What do I do if I need an accommodation?
In compliance with the ADA Amendments Act (ADA), if you have a disability and would like to request an accommodation in order to apply for a position with Mississippi State University, please contact the Department of Human Resources Management at tel: (662) 325-3713 or ada@hrm.msstate.edu .
If you have any questions regarding this policy, contact the Department of Human Resources Management at (662) 325-3713 or ada@hrm.msstate.edu . Upon request, sections of this job listing are available in large print, and readers are available to assist the visually impaired.
