The Andersson lab is looking to recruit a highly motivated and talented PhD student to focus on enhancers and transcriptional regulatory variation.
Context
The lab of Robin Andersson focuses on genomics and computational/statistical modeling of transcriptional regulation based on large-scale sequencing data, including experimental data generated from within the lab. We aim to characterize and better understand the architectures and complexities of transcriptional regulation and gain insights into the mechanisms of regulation. We further focus on the fundamental properties of enhancers and promoters as well as the biogenesis and characteristics of enhancer RNAs. For more information, see http://anderssonlab.org.
The lab is based in a highly collaborative environment in the Bioinformatics Centre at the Department of Biology, University of Copenhagen, Denmark.
Project
The correct function of regulatory elements and their interplay are essential for the precisely coordinated transcriptional activities within a cell. Disrupted regulatory activities may therefore have detrimental effects leading to disease. However, most variants have no or an only weakly associated trait and, in general, the impact of genetic variants on regulation is not well understood. Therefore, using our established accurate transcription-based method to assess activities of regulatory elements and the associations between them, we aim to systematically characterize human regulatory variation and its consequences. We further aim to infer models describing the function of a regulatory element and its importance, and thus the impact on regulation upon disruption.
The successful candidate is expected to work on projects related, but not limited, to
- computational modeling of enhancer regulation and genome-wide mapping of enhancer architectures
- assessment of the extent and impact of individual variation and genetic variants in regulatory elements in order to understand their importance, stochasticity and robustness
Qualifications
The successful candidate should have a computational and/or statistical background and experience with analysis of large-scale data. Experiences with DNA or RNA sequencing data, genotyping data, statistical genetics, computational modeling, machine learning and/or statistical learning techniques are considered a major plus. Importantly, the candidate should have a strong interest in transcription and transcriptional regulation.
Specifically, the candidate should meet the following requirements:
- A MSc in Bioinformatics, Computational Biology or in a related quantitative field to be able to quickly acquire Bioinformatics computational skills
- Excellent programming and data analytical skills
- Fluent English
See full job description and apply online (deadline October 31, 2016) at http://employment.ku.dk/phd/?show=857805.
