Postdoctoral Fellow in Quantitative Models for Predicting Antibiotic Resistance

The Wellcome Trust Sanger Institute is seeking a highly motivated researcher with strong skills in computational genomics to fill a postdoctoral fellow position. The aim of the fellow is to develop a quantitative framework for predicting antimicrobial resistance spread in clinical bacterial isolates from diverse generated large-scale genetic and phenotypic data.
The goal of the encompassing international collaborative project is to predict and map drug targets for cell-to-cell horizontal transmission of antibiotics resistance. To this end, we are generating data from three different types of bacterial strains. First, we are performing large-scale experimental evolution experiments to map de novo mutations that confer changes to transmission ability. Second, we are phenotyping comprehensive collections of knockout and overexpression mutants to identify determinants of adaptation. Finally, we will sequence full genomes of, gather gene expression and proteomics data for, and deeply phenotype thousands of clinical isolates from the largest collection in Europe to find variants likely to alter resistance transmission properties. The first sets of experiments have been executed, and the bulk of the assays are expected to complete in 2017.
The successful candidate will perform original research in quantitative modeling of these multimodal high throughput data to predict antimicrobial transmission for previously unobserved clinical isolates. It is important you have the ability to bridge from understanding the processes generating the measured data, to implementing computational pipelines to extract information, as well as creating and applying correct models for analysis. You are expected to make progress on your project as the first priority, while budgeting time for training in further skills, piloting new leads, and potentially collaborating on other related projects. To function effectively in a multidisciplinary, collaborative setting, you have to be able to communicate well with scientists from diverse backgrounds, and be a pleasant colleague.
This position offers the opportunity to work at one of the world’s leading genomic centres at the forefront of genomic research, in collaboration between computational groups with expertise in quantitative genomics (Parts, Sanger Institute) and evolutionary biology (Mustonen, University of Helsinki). You will have access to Sanger's computational resources, including a 15000+ core computational cluster, the largest in life science research in Europe, and multiple petabytes of high-speed cluster file systems. Our group also has laboratory space and access to core facilities, where we generate our own data with the help of dedicated staff. This provides an exciting opportunity for you to not only analyse the data, but to be actively involved in the planning and execution of large-scale experiments.
We are part of a dynamic and collaborative environment at the Genome Campus and, although we seek someone who can work independently, you will have the opportunity to interact with researchers across many Programmes at the Institute. In particular, we often share interests with colleagues from other teams in the Cellular Genetics and Pathogen Genomics Programmes, as well as our neighbours at the European Bioinformatics Institute.

Essential Skills
Motivation to understand antibiotic resistance spread
PhD in a relevant subject area (Physics, Mathematics, Computer Science, Engineering, Statistics, Computational Biology, Bioinformatics, Molecular Biology)
Experience with bacterial genomics
Ability to devise novel quantitative models, use relevant mathematics-heavy literature
Experience in formulating the world in statistical models and applying them to real data
Full working proficiency in a scripting language (e.g. Python, R, Perl), and UNIX/Linux
Ability to work independently, organise workload, and communicate ideas and results
Strong publishing record

Ideal Skills
Knowledge of genomics and molecular biology
Previous experience in creating finished software
Full working proficiency in a compiled language (e.g. C, C++, D, Julia, Fortran)
Previous experience with implementing–omics data analysis pipelines on a cluster
Proven independent working style, problem solving, data analysis and generation of novel ideas.

Other information
Postdoctoral Fellows are typically in their first or second postdoctoral position as part of a period of early career research training. The Sanger Institute is a charitably funded research centre that applies the power of genomics to uncover the basis of genetic and infectious disease. We conduct science at a scale and speed that sets our research apart. Our passion is to provide results that can be translated into diagnostics, treatments or therapies that reduce global health burdens. The Institute is located near Cambridge on the stunning Wellcome Trust Genome Campus. This growing and dynamic site is the British hub of genomic science. It hosts the European Bioinformatics Institute (EBI), the Centre for Therapeutic Target Validation, a Biodata Innovation Centre and will soon host Genomics England Limited’s 100,000 Genomes Sequencing Centre. It is an excellent environment in which to work and collaborate with researchers on campus and around the world and benefit from cross-fertilisation of ideas. To help researchers to develop their skills and networks, the Institute hosts a range of scientific seminars with internal and invited speakers, scientific group meetings and skills development workshops. In addition the Campus is home to the Wellcome Trust Advanced Course and Scientific Conferences programme and the Wellcome Trust Conference Centre. Our Benefits include: Defined Benefit Pension Scheme, Group Income Protection, Healthcare scheme, Childcare Vouchers, Nursery and 25 days Annual Leave plus Bank Holidays. We also have a gym, two cafes, a nursery, dining facilities, and a free campus Bus service. Our thriving Sports and Social Club provides many opportunities to meet with people working across the campus.