Cancer Genome Analyst - London
I am currently recruiting for a Genomics Data Scientist for a very well known and respected client based in London.
They are looking for Genomics Data Scientists who investigate and develop solutions to extract more information from the genome (alignment and variant calling) and to interpret the genome in the context of a persons clinical features.
Genomics Data Scientists work as part of squads building translating state of the art analytics into clinically-fit production quality solutions.
Essential skills required;
•[RD] Excellent knowledge and experience in one or more areas of human DNA analysis, such as rare disease genomics, family-based analysis, genetic association testing, risk score prediction, structural variation, pharmacogenomics, typing of complex genomic regions such as HLA/KIR
•[Cancer] Excellent knowledge in cancer genomics, approaches to call somatic variation and interpret cancer genomes.
•Strong knowledge of statistics and/or machine learning
•Strong knowledge of high throughput sequencing algorithms and available resources. Experience with full cycle of analysing NGS data from sequencing QC to annotation and prioritisation of variants.
•Strong programming skills (Python, R)
•Excellent technical writing skills
•A decent publication record demonstrating their ability to conceive and carry to conclusion scientific investigations
•Excellent ability to represent and visualise data to derive insights
•A demonstrable ability to cope under pressure and deliver to deadlines
•Experience in handling large data sets
•Ability to communicate effectively within a multidisciplinary team
•Flexible and co-operative approach to colleagues
•Experience and flexibility to collaborate on code with others including good working knowledge of Git
•Ability to work independently and to show initiative within a team
•Ability to prioritise and balance competing demands
•PhD experience of working within Rare Diseases or Cancer Bioinformatics/Computational Biology/Systems Biology/ or equivalent work experience
•Ideally undergraduate studies in a strongly quantitative discipline such as (e.g. physics, computer science, or maths). These skills could also have been developed, for example, through a PhD in computational biology, statistical genomics, or statistical genetics.
Key relationships to reach solutions;
•Genome analysis chapter for methods, approaches, standards
•Squad for day to day work
•Members of the clinical and science directorate for clinical applicability / sanity checking
•Members of the GLH community to truly understand what their needs are and discuss how they can be met
•Collaborate with external members of the genome analysis community including but not exclusive of GECIP collaborators to address outstanding scientific or technical challenges
This is a great opportunity and in return they offer,
A competitive salary
30 days holiday
A generous pension scheme
Individual learning budgets for every colleague
Plus many more.....
If you wish to discuss this fantastic opportunity further give me a call on
t: +44 (0)121 616 3404 | m: +44 (0)7985 635091 or Email email@example.com
Key words: Bioinformatics, Bioinformatician, Diagnostics, Oncology, Cancer, Data Science, Machine Learning, PHD, Post-Docs, Cambridge, Algorithm, Statistical Genetics, NGS, Genomics, Computational Biology, R&D, Data Scientist