Research Associate in Cancer Bioinformatician
The Cancer Bioinformatics group (http://cancerbioinformatics.co.uk/) within the Breast Cancer Now Unit, School of Cancer and Pharmaceutical Sciences, at King’s College London, is currently seeking a Research Associate with expertise in genomics and machine learning in the field of translational cancer research to join our efforts in understanding the molecular and mechanistic basis of triple negative-breast cancer.
This applicant will join a multidisciplinary team of researchers whose collective aims are to implement analytical approaches for the integrative analysis of multi-omics data from model systems and patient studies of triple-negative breast cancers. The project will entail developing and implementing innovative computational strategies for the identification and integration of genomic instability patterns derived from DNA double-strand break and whole-genome sequencing data, which will then be associated with digitised morphological image data of primary tumours. The post will be supervised by Dr. Anita Grigoriadis.
Applicants should have a strong computational background and expertise in dealing with large genomics datasets. Excellent programming, data analysis and machine learning skills are required. Experience with diverse sequencing data is desirable. Applicants will hold a postgraduate degree or equivalent experience in a relevant role. The ideal candidate should be passionate about translating genomics into clinical practice and highly motivated to work in a fast-paced and highly collaborative environment.
The post will be based in Dr Grigoriadis’ Cancer Bioinformatics Team at Guy’s Cancer Centre at Guy’s Hospital and will also involve interaction with colleagues based in the Breast Cancer Now Unit at KCL and the Breast Cancer Now Research Centre at the Institute of Cancer Research, London.
This post is Full Time on a FTC.
• To be able to implement, adapt and develop novel bioinformatics methodologies.
• To be able to use standard statistical and machine learning approaches.
• To be responsible for establishing workflows to process genomics data, integrating multi-omics data, interpreting results and corroborating findings in external datasets.
• To prepare data and workflows to analyse that data in such a way that it can be shared with other collaborators.
• To oversee the maintenance of information and documentation regarding the implemented approaches and developed methods.
• To provide independent advice and deal with scientific and technical queries regarding data analysis and computational biology.
• To be able to explain high-dimensional data analysis to computational biologists, bioinformaticians and non-computational biologists.
• To prepare his/her work in the form of a manuscript for publications and presentation at local and international research meetings.
• To present results during group meetings and in written/figure form where necessary.
• To contribute to discussions with research colleagues to identify and design appropriate experiments.
• To contribute to the production of research reports and publications.
• To form effective networks with colleagues in other groups of the department and with peers in King’s College London to ensure smooth and effective running of the group’s facilities and to identify opportunities for the group to benefit from facilities elsewhere.
• To work with other members of the team to generate data.
Skills, knowledge, and experience
- A relevant postgraduate degree or equivalent experience in a relevant role.
- MSc in computer science, bioinformatics or any other bioscience with a strong numerate component such as mathematics or statistics.
- BSc in computer science, bioinformatics, statistics or a similar academic field.
- Previous experience with DNA sequencing data.
- Understanding of genomics, including genomic instability and DNA damage repair.
- Fluent in at least one statistical programming language (e.g. R or Matlab).
- Fluent in as least one programming language (e.g. Shell, Perl, Python, or C++).
- Experience with machine learning libraries (e.g. Scikit-learn, Pytorch, Tensorflow)
- Experience with HPC environments.
- Excellent interpersonal and communication skills and the ability to liaise with other group members.
- Highly self-motivated and hard working.
- Ability to present complex data at meetings (internal and external audiences, including international conferences).
- Ability to analyse data, meet deadlines, and write up results in a timely manner.
- Writing and publishing high-quality research in peer-reviewed journals.
- Experience in collaborating with clinicians and wet-lab scientists.
- Motivated to achieve further training in advanced bioinformatics.
- Ability to prioritise workloads, meet deadlines and organise work accordingly.