Applications are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme. The position is available from 1 July 2022 or later.
Research area and project description:
We are looking for a talented and creative PhD student to contribute to the SIEVE project (“Selection of mutations by in silico and experimental variant effects: a new strategy to improve fitness in cool-season grasses”). The SIEVE project is supported by an Emerging Investigator grant by the Novo Nordisk Foundation, which funds groundbreaking research with promising applications in data science and the green transition in Europe.
The PhD student will be involved in an innovative research project in statistical genetics and computational biology applied to a model species (Brachypodium). She/he will evaluate the impact of mutations by analyzing multi-omics data in mutant populations: (i) whole-genome sequencing; (ii) RNA expression; (iii) metabolomics; and (iv) physiological measurements. These analyses will benefit from expertise in statistical genetics (e.g., quantitative genetics, population genetics, evolutionary genomics) and/or computational biology (e.g., bioinformatics, machine learning, network analysis).
Under the SIEVE project, we will detect impactful mutations by machine learning and evolutionary genomics across species. We will focus on cool-season grass species, which include the model species Brachypodium as well as important crop species like wheat and barley. A key contribution of the project will be the validation of detected mutations at single-site resolution, to support the application of novel detection methods in genomic prediction or CRISPR-based editing. The selected PhD candidate will lead this effort of validation, by analyzing multi-omics data in mutant populations, or additional datasets in natural populations.
We encourage candidates to submit a description of proposed research for the validation of predicted genetic effects in mutant or natural populations. Candidates are welcome to contact Guillaume Ramstein for information about the SIEVE project or this PhD position.
Qualifications and specific competences:
Candidates must hold (or be expected to hold) a Master’s degree in a field related to statistical genetics (e.g., quantitative genetics, population genetics, evolutionary genomics) or computational biology (e.g., bioinformatics, machine learning, network analysis).
The ideal candidate will also demonstrate some knowledge of scripting/programming languages (e.g., in R, Python, Java or Shell), previous research experience in relevant fields, and good communication skills in English.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Center for Quantitative Genetics and Genomics, Ole Worms Allé 3, Building 1171, 8000 Aarhus, Denmark.
How to apply:
Please follow this link to submit your application.