Postdoctoral Fellow - Bacterial Evolutionary Biology
Salary in the region of £31,503 - £39,492 (dependent on experience) plus excellent benefits
Fixed term for 3 years
We are seeking a talented, motivated scientist with a strong interest in, and experience of, analyzing genomes and large genomic datasets to gain insights into the patterns and drivers of pathogen evolution. Ideally you would have biological or mathematical/statistics background with a demonstrated interest in developing bioinformatic skills or have proven track record of applying existing skills toward the analysis of complex genomic datasets.
The position you are applying for falls within the Bacterial Genomics and Evolution faculty team, under the leadership of Professor Nick Thomson. We use genomic approaches to explore questions of basic science relating to the evolution and spread of bacterial pathogens in both humans and animals. We have established, over many years, strong collaborations with groups working on infectious diseases in local as well as national public health settings, NGO’s and leading research institutes around the world, providing access to people, resources and incredible datasets. We have a specialist interest in the evolution and spread of diarrhoeal disease (both the pathogen[s], their host[s] and the role of the microbiota) and tropical diseases. The team has a broad range of lab and informatics experience, and works collaboratively to analyse complex datasets with a history of developing novel informatics and lab-based approaches for accessing genomic and transcriptomic data.
To help you see the type of work we have been doing, here is a selection of the team’s most recent publications.
Tropical and diarrhoeal diseases:
- Marks et al., (2018) Direct Whole-Genome Sequencing of Cutaneous Strains of Haemophilus ducreyi. Emerging Infectious Disease.
- Marks et al., (2018) Diagnostics for Yaws Eradication: Insights From Direct Next-Generation Sequencing of Cutaneous Strains of Treponema pallidum. Clinical Infectious Disease.
- Hadfield (2017) Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion. Genome Research.
- Domman et al., (2017) Defining endemic cholera at three levels of spatiotemporal resolution within Bangladesh. Nature Genetics
- Domman et al., 2017 Integrated view of Vibrio cholerae in the Americas. Science
Methods lab and in silico:
- Page et al., (2018) PlasmidTron: assembling the cause of phenotypes and genotypes from NGS data Microbial Genomics
- Seth-Smith Generating whole bacterial genome sequences of low-abundance species from complex samples with IMS-MDA. Nature Protocols.
- Baker S. et al., (2018) Genomic insights into the emergence and spread of antimicrobial-resistant bacterial pathogensScience
- Baker K., et al., (2018) Horizontal antimicrobial resistance transfer drives epidemics of multiple Shigella species. Nature Communications.
In addition, these are important papers from other groups chosen to give you a sense of the team’s broader interests and areas/themes that they may wish to explore.
- Chen & Shapiro (2015) The advent of genome-wide association studies for bacteria. Current Opinion in Microbiology
- Sela, et al. (2016) Theory of prokaryotic genome evolution PNAS
- Peischl et al. (2016) Genetic surfing in human populations: from genes to genomes. Current Opinion in Genetics & Development
- Richardson et al. (2018) Gene exchange drives the ecological success of a multi-host bacterial pathogen. Nature Ecology and Evolution
- Harkins et al. (2017) Methicillin-resistant Staphylococcus aureus emerged long before the introduction of methicillin into clinical practice Genome Biology
- Corander et al. (2017). Frequency-dependent selection in vaccine-associated pneumococcal population dynamics. Nature Ecology & Evolution
If you wish to highlight a possible area of interest based on any of the papers above for further discussion, if shortlisted for an interview, please do highlight this in your application.
This position would place you within a Faculty team within the Parasites and Microbes Programme, all set within a world leading genomics institute. You would be working closely with informaticians, wet-lab biologists, Postdoctoral Fellows and PhD students within the group and across this programme. You will be required to coordinate analysis of multiple project datasets and identify and establish new collaborations and projects, as well as to form part of an integrated team. The candidate will have substantial support and opportunities to broaden their skill-set and further their career.
- Ph.D. in biological or mathematical/statistics discipline
- The ability to analyse and interpret genomic data with strong quantitative/computational skills
- Detail oriented and highly organised
- Self-motivated, able to work independently and organise own workload
- Ability to prioritise
- Ability to interact professionally and productively with other members of a team
- Data handling skills
- Proven track record of publishing papers
- Excellent communication skills
- Interest in mentoring and developing others
- Experience developing novel approaches to analysing genomic sequence data
- Experience working with international collaborators
The Wellcome Sanger Institute is a charitably funded research centre and committed to training the next generation of genome scientists. Focused on understanding the role of genetics in health and disease and a world leader in the genomic revolution, our mission is to use genome sequences to advance understanding of human and pathogen biology in order to improve human health. We aim to provide results that can be translated into diagnostics, treatments or therapies that reduce global health burdens. Our science is large-scale and organised into Programmes, led by our Faculty who conceive and deliver our science, and supported by our Scientific Operations teams responsible for all data production pipelines at the Institute.
Our Campus: Set over 125 acres, the stunning and dynamic Wellcome Genome Campus is the biggest aggregate concentration of people in the world working on the common theme of Genomes and BioData. It brings together a diverse and exceptional scientific community, committed to delivering life-changing science with the reach, scale and imagination to pursue some of humanity’s greatest challenges.
Our Benefits: Our employees have access to a comprehensive range of benefits and facilities including:
- Group Defined Contribution Pension Scheme and Life Assurance
- Group Income Protection
- Private Health Insurance
- 25 days annual leave, increasing by one day a year to a maximum of 30
- Family friendly environment including options for flexible and part-time working, a childcare voucher scheme, Campus Nursery and Summer holiday club
- Two days paid Employee Volunteering Leave a year
- Employee Discount Scheme
- Campus Gym, tennis courts, cricket pitch and sports hall plus a range of dining facilities
- Active Campus Sports and Social Club
- Free Campus Bus Service
Genome Research Limited is an Equal Opportunity employer. As part of our commitment to equality, diversity and inclusion and promoting equality in careers in science, we hold an Athena SWAN Bronze Award and have an active Equality, Diversity and Inclusion programme of activity. We will consider all applicants without discrimination on grounds of disability, sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law. We are open to a range of UK-based flexible working options including part-time or full-time employment as well as flexible hours due to caring or other commitments.
Please include a covering letter and CV with your application. Optionally, a brief project idea can also be submitted to describe how you would contribute to the team.
The closing date is 16th October however applications will be reviewed on an ongoing basis.