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Bioinformatics,PhD position in statistical genetics and computational biology – Aarhus, Denmark 2022

Aarhus University (AU), Denmark

Applications are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme.

Title:PhD position in statistical genetics and computational biology: analysis of multi-omics biological data in novel populations of Brachypodium

 

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General Info

Position: PhD
No. of Positions: 1
Research Field: , , , , ,
Joining Date: July 01, 2022
Contract Period: -
Salary: According to Standard Norms

Workplace:
Graduate School of Technical Sciences,
Center for Quantitative Genetics and Genomics
Aarhus University (AU)
Aarhus C, Denmark

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Qualification Details

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.

Responsibilities/Job 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.

How to Apply?

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Reference Number: -
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Documents Required

Please follow this link to submit your application. Application deadline is 28 February 2022 23:59 . Preferred starting date is 1 July 2022.

For information about application requirements and mandatory attachments, please see our application guide.

About the Employer: Aarhus University (AU)

Note or Other details

Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.

All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.  

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.


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Contact details

Applicants seeking further information are invited to contact:Professor Torben Asp, torben.asp@qgg.au.dk or Assistant professor Guillaume Ramstein, ramstein@qgg.au.dk

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