Research Associate - Bioinformatician for Proteomics

University College London - Research Department of Cancer Biology

The UCL Cancer Institute was established in 2007 and is the hub for cancer research at UCL. UCL is consistently ranked within the top 20 global universities. The Cancer Institute is part of the Faculty of Medical Sciences, within the School of Life and Medical Sciences. This School comprises the largest concentration of biomedical researchers in Europe. The Cancer Institute hosts the majority of cancer research at UCL, whilst other cancer activities across the UCL campus form part of a recently established Cancer Domain. The overall remit of the Institute is to develop a cancer presence and excellence, which rival other major national and international hubs for cancer research. Within the Cancer Institute, computational research is focused at the Bill Lyons Informatics Centre (BLIC), which provides a base for bioinformaticians and computational biologists with expertise in cancer genomics.

Duties and responsibilities of the post holder include but are not limited to: consult with researchers regarding the optimal experimental design and to prepare a protocol of data collection and analysis; to conduct and lead the analysis of protein-protein interaction, protein abundance and protein post-translational modification data by using open source, in-house, and third party algorithms; to develop and execute computational workflows for the analysis of large scale label-free and label-based mass spectrometry data; to integrate multidisciplinary data, e.g. from genomics and proteomics in the context of the same project.

The post is initially funded until 31st March 2022.

The successful candidate must hold PhD in Bioinformatics or Biostatistics, or a relevant discipline, degree in Statistics or a relevant discipline, have substantial experience with statistical programming in R; knowledge of scripting and programming languages such as Perl, Python or C++ in a Linux environment. Relevant experience as demonstrated by publication output, proficient in the use of Excel (for recording & data analysis), sound, up-to-date understanding of Health & Safety legislation and its application in a modern laboratory are also essential requirements. Knowledge of machine learning algorithms and Bioconductor packages, understanding of information technology processes such as software, database and web development, experience with the analysis of mass spectrometry-based proteomic data (DDA, SRM/PRM, and/or DIA) are desirable criteria.

UCL vacancy reference: 1683056

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button below.

For informal enquiries please contact Silvia Surinova ( For enquiries, regarding the application process, please contact Laime Matkeviciute (HR Assistant),

Closing Date: 12 November 2017

Interview Date: 8 December 2017 

Latest time for the submission of applications: 23:59.

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