PhD Position in Modelling Marine Larval Dispersal and Spatial Population Genetics and Demography
Location: Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. 
Supervisor: Dr. Scott Burgess (https://www.ntnu.edu/employees/scott.c.burgess)
Application due date: 20 October 2026.
Topic: The overall aim is to provide new understanding of the processes that affect marine larval dispersal and gene flow, how we measure it with genetic data, and how we use that information to predict the genetic and demographic responses of spatially structured marine populations to environmental variation and change. Specifically, the primary focus of the PhD will be to understand how complex coastlines, ocean circulation, and biology (e.g., reproductive systems and phenology, larval behavior and survival) interact to affect the spatial structure of the genetic and demographic properties of marine populations. There is flexibility, and an expectation, for candidates to develop their own line of research within this broad scope. For example, projects could focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal distances from the spatial structure of genetic genealogies across the genome, and the genetic relatedness among individuals; or develop and use biophysical models (hydrodynamics + particle tracking) to understand the demographic and genetic dynamics of marine metapopulations and adaptation to environmental change. The PhD position provides an exciting opportunity to gain broad experience and expertise working at the interface of population genetics and demography, oceanography, and computer science. It will provide broad training in research skills, and will suit a candidate who is curious and is motivated to undertake high-level research to gain skills in computational methods and software tools to understand large, complex biological data.

The candidate must have:
- a relevant background in evolution or ecology
- quantitative and computational skills.

The candidate should also meet at least some of these points:
- Experience with computer coding, such as R, Python, or MATLAB, and Linux command-line tools including Bash scripting and running analyses on high-performance computing systems. 
- Experience with, or ability to learn, the evolutionary simulation software SLiM (Selection on Linked Mutations), or similar.
- Experience applying machine learning techniques, or the ability to learn them.
- Experience using biophysical dispersal models, or the ability to learn to use them.
- Experience working with geospatial data and spatial analysis, or the ability to learn.
- Experience analysing whole genome libraries, including quality control, sequence alignment, and calculating population genetic summaries.

NTNU’s Department of Biology hosts internationally leading research activity in ecology, evolutionary biology, physiology, marine science and technology, and cell & molecular biology. The position will be hosted within a dynamic international research group based at NTNU, with strong links to local and international collaborators. NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of roughly 200,000. The Norwegian welfare, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities to enjoy nature, culture and family life and has low crime rates and clean air quality. Trondheim has excellent bicycling and public transport options, making it easy to get around town without a car.

For more information, including how to apply, please visit: https://www.jobbnorge.no/en/available-jobs/job/308848/phd-candidate-in-modelling-marine-larval-dispersal-and-spatial-population-genetics-and-demography

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