We are looking for an ambitious computational biologist to take a leadership role in identifying distinct patterns of mutations that occur and discerning the processes that generate them. You will be joining a successful and well resourced group of computational biologists in the highly collaborative and collegiate environment of the MRC Human Genetics Unit (HGU). Complementing the computational environment there is great scope for commissioning or collaborating to generate novel data to support the project and test hypotheses, validating our findings and maximising the impact of our discoveries.
The research environment is multidisciplinary and applicants with PhDs in the biological, physical, computational or mathematical sciences are welcome, but a good understanding of genome biology and large scale computational analysis is essential.
For further information about the laboratory of Professor Martin Taylor please visit taylor.igmm.ed.ac.uk
The appointment will be for 3 years in the first instance and is available immediately. Full details are available here:
www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=040487
Required Knowledge, Skills and Experience:
• PhD or near completion in a biological, mathematical, computational or related scientific field. Extensive research experience in computational genomics or a related discipline.
• Experience and demonstrated success in leading aspects of research projects evidenced by prominent authorship of peer-review publications.
• Extensive expertise in using computational tools and bioinformatics to interrogate the patterns of DNA sequence change.
• Experience in handling and analysing large datasets including the primary analysis of high-throughput sequence data.
• Proven expertise in Perl, Python or a related programming language.
• Extensive experience in the use of R for data interrogation and presentation.
• Ability to work in multiple computer operating systems, including Linux and the Unix command line environment.
• Proven ability to communicate complex information clearly to an audience and in writing.
• Experience of successful student supervision and effective resource management.
Desirable Knowledge, Skills and Experience:
• A strong background in evolutionary genomics in a species, population or cancer setting.
• Understanding of cellular molecular processes such as DNA replication, repair, chromatin packing and transcription.
• Knowledge of evolutionary and population based measures of selection.
• Experience in machine learning and pattern deconvolution methods.
Please apply online via the University of Edinburgh jobs site:
www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=040487