Research Fellow in Computational Biology

2 weeks ago

Edinburgh, United Kingdom University of Edinburgh Full time

**Research Fellows (Computational Biologists)**

**UE07: £36,333 - £43,155 Per Annum**

**College of Medicine and Veterinary Medicine - CGEM / IGC**

**Full Time, Fixed Term for 12 months**

**The Opportunity**

NTU Lee Kong Chian School of Medicine (LKCMedicine) and University of Edinburgh (UoE) are leading research-intensive Institutes of Higher Learning. Both Universities have dynamic research environments with many areas of complementary and overlapping activity. In particular, the Universities have large scale population health research programmes, coupled to well-established health data platforms, and advanced techniques in genomics. This includes the SG100K study of 100,000 Asian individuals in Singapore (hosted by LKCMedicine) and the Generation Scotlans study of 24,000 people in Scotland. The two Universities are therefore well positioned to collaborate on population and genomic research to address non-communicable disease, taking advantage of the insights generated from epidemiological studies that straddle ethnic groups.
- Precision Medicine. Develop predictive models that improve identification of clinically important variants in genes of specific relevance to clinical care (e.g oncology, rare disease) in the Asian populations.
- Cognitive Health. Provide new insight into the causal relationship between DNA methylation and cognitive decline in Alzheimer’s patients and identify population level commonalities and differences in that relationship.
- Molecular epidemiology of skin disease. Improve our understanding of the role of genetic and epigenetic mechanisms in the development of atopic dermatitis, and provide new insights into the pathophysiology of atopic skin inflammation.

**Key responsibilities include but not limited to**:

- Analyse pathogenic protein-coding mutations, using structural bioinformatics, molecular modelling and variant effect prediction to both identify disease-associated variants, and to understand their molecular mechanisms.
- Build databases containing the genomic datasets, write scripts to analyse the information in the dataset and queries to retrieve the information
- Imputation of missing data
- Present results within the research group, using appropriate presentations formats;
- Participate in seminars and work-in-progress meetings within the team and collaborators.
- Provide guidance and mentorship to junior researchers, undergraduate and graduate students, occasional educational and or instructional activities.

**Skills and knowledge**:

- Experience with R/Python/Java or similar languages and with Unix based platforms
- Knowledge of next generation sequencing (genomics, bulk and/or single cell transcriptomics), population genetics, statistics, bioinformatics or high dimensional data analysis
- Demonstrated in-depth knowledge, skills and expertise, with capability of leadership and achieving research excellence

Click **here **for a copy of the full job description

**As a valued member of our team you can expect**:
An exciting, positive, creative, challenging and rewarding place to work. We give you support, nurture your talent and reward success. You will benefit from a competitive reward package and a wide range of staff benefits, which includes a generous holiday entitlement, a defined benefits **pension scheme **, **staff discounts, **family friendly initiatives **, flexible working and much more. Access our **staff benefits page **for further information and use our **reward calculator **to find out the total value of pay and benefits provided.

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our **right to work **webpages

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