Postdoc Position in Bayesian Analysis of Childhood Asthma is available at the Section for Bioinformatics, DTU Health Tech, Denmark (Health Technology, Bioinformatics Jobs)
Deadline to Apply
Apr 28, 2021 (23: 59 GMT +1)
|No. of Position(s)||1|
|Research Area||– Bioinformatics|
|Salary||According to standard norms|
|Workplace||DTU Health Tech|
Technical University of Denmark
|Contract Period||2 Year|
|Starting date||Not Specified|
- PhD degree (or equivalent)
- The applicant must have strong computational skills, and a solid background in bioinformatics and genetics. It is required that the applicant has experience both in general purpose programming languages (e.g., Python or C++) and in probabilistic programming languages (e.g., Stan or Pyro).
Responsibilities/ Job Description
The focus of the project is Bayesian statistical modelling of pediatric asthma. The aim of the project will be to integrate multiple types of data (genomic, microbiome, demographic, patient records, pathway, protein-protein interaction data, etc) in a systems biology framework to investigate the molecular mechanisms underlying the development of childhood asthma.
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.
Applications must be submitted as one PDF file containing all materials to be given consideration. The file must include:
- Application (cover letter)
- Academic Diplomas (MSc/PhD)
- List of publications
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.
About Research project
With respect to the impact of genetics, we have a special interest in the detection of interactions and epistasis: Most GWAS studies focus on single nucleotide polymorphisms (SNPs) one at a time. However, the biological reality is likely to be that traits are typically influenced by the combined impact of several SNPs, each having a weak effect. An important part of the present project will be to develop methods for detecting such sets of interacting SNPs using methods from within the Bayesian, probabilistic modeling paradigm. The aim is to explore both hypothesis-free approaches as well as methods based on understanding of the investigated biological systems (e.g., basing the search for SNPs on knowledge of biological pathways or protein-protein interaction data)
The use of mechanistic, Bayesian models (e.g., using the probabilistic programming language Stan) will be an important tool.
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.
Professor Anders Gorm Pedersen
Post expires at 8:59am on Thursday April 29th, 2021 (GMT+9)