Computational population genetics – Postdoc position to develop algorithms and computational methods to deal with the analysis of large datasets from modern and ancient sources, at DTU Health Tech, Technical University of Denmark, Denmark
Deadline to Apply
June 10, 2021 (23: 59 GMT +1)
|No. of Position(s)||1|
|Research Area||– Computational population genetics|
– Biological science
– Computer science
|Salary||According to standard norms|
|Workplace||DTU Health Tech|
Technical University of Denmark
|Contract Period||3 Years|
|Starting date||Sep 01, 2021|
You must hold a PhD degree (or equivalent) ideally in biological science with a focus on quantitative and mathematical aspects, or in computer science or mathematics.
The candidate we are looking for should ideally have the following qualifications:
- Knowledge of a programming language like Python, Perl, C++ and/or Java
- Ability to work in a UNIX environment, ideally in a high-performance computing environment
- Ideally, proficiency in C/C++ or Java or similar is a plus (not required)
- Thorough understanding of basic principles of population genetics
- Knowledge of probabilities and statistics
- Firm grasp of first-year university mathematics (differential calculus/linear algebra)
- Knowledge of coalescence theory or diffusion theory is an advantage
- Expertise in next-generation sequencing data generation and processing are also a plus
Responsibilities/ Job Description
In this position you will develop algorithms and computational methods to deal with the analysis of large datasets from modern and ancient sources. More specifically, these algorithms will be aimed at analyzing a large number of ancient genomes using population genetics methods. The bioinformatics section of DTU Health Tech performs research in the areas of different metagenomics, machine learning, cancer genomics and population genomics. Additional information should be obtained by contacting the potential main supervisor directly. The university is located in the greater Copenhagen area, which is acknowledged for its excellent standards of living, childcare and welfare system.
Current bioinformatics algorithms and software are often ill-equipped to deal with DNA extracted from ancient populations. This ancient DNA shows high levels of fragmentation and accumulated chemical damage. Furthermore, the number of individuals that can be sequences is often limited. Fortunately, several problems pertaining to ancient DNA and ancient paleogenetics can be described in a maximum-likelihood framework and computer science techniques can help us to solve such numerical problems efficiently via machine learning, numerical algorithms and data structures. You will work in collaboration with other partners including the University of Copenhagen in order to develop the next generation of algorithms and software applied to DNA from fossils which can then be used to reconstruct population history and infer selection.
Given the COVID19 pandemic, we will happily accommodate requests for remote work until in-person work is deemed safe.
How to Apply?
To apply, please open the link “Apply online”, fill out the online application form, and attach all your materials in English in one PDF file
- A letter motivating the application (cover letter)
- Curriculum vitae
- Academic Diplomas (MSc/PhD)
- List of publications
About DTU Health Tech
DTU Health Tech creates health technology to improve health and well-being for humans in collaboration with companies, hospitals as well as national and international researchers. The cross-disciplinarity at the department, which includes mathematics, computer science, physics, chemistry and biology, provides the foundation for new and innovative technology for the future.
- The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.
- If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.
Prof. Gabriel Renaud
Post expires at 8:59am on Friday June 11th, 2021 (GMT+9)