Postdoc in Epigenomics and Systems Biology of Cattle Artificial Reproduction Technology

Applicants are invited to apply for a postdoctoral position in computational biology at Technical University of Denmark. This fellowship is last for 24 months and posible to extend. Potential candidates should apply before February 08, 2019.

The group of quantitative genomics, bioinformatics and computational biology (QBC) (Section of Statistics and Data Analysis) is looking for a highly talented postdoc for 24 months to mainly work in the externally funded research project, EliteOva ( ), headed locally by Professor Haja Kadarmideen at DTU Compute and by the overall project leader, Professor Poul Hyttel, based at the Department of Veterinary and Animal Sciences (IVH) ( ) at the University of Copenhagen (KU).

The postdoc position will have a strong collaboration with the KU-IVH and be part of the working environment there as well as having close interactions with all EliteOva's consortia partners.

The postdoc will be expected to: This job description is only an outline of the main tasks, but the jobholder will carry out any other duties that may be reasonably required.

Candidates should have a PhD degree combining genome-informatics, bioinformatics, computational biology or systems biology with animal biosciences with special emphasis on reproduction and embryotechnology. The ideal candidate profile is a combined expertise of bioinformatics and molecular biology working on animal epigenetics / animal reproduction. Epigenomic, transcriptomic and genomic data analyses (e.g. RRBS, RNAseq, SNP array/genome sequence data) as well as integrative systems biology analyses will specifically be in focus.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

QBC group is involved in the cutting edge research at the interphase of Quantitative or statistical genetics, Bioinformatics and Computational Biology in clinical, experimental, population-wide studies. We model and analyse vast amount of high-throughput SNPchip genotypic data, exome or whole genome or transcriptome or epigenome or metagenome sequence data and other multiomics datasets that are collected from a large number of (related) individuals measured for phenotypes or diseases. We work with data from farm animals, animal models for human diseases and directly from human populations. DTU Department of Applied Mathematics and Computer Science (DTU Compute) has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses in mathematics, statistics, and computer science to all engineering programs at DTU and specialized courses to the mathematics, computer science, and other programs. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.


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