Are you interested in studying metagenomic derived protein families and developing methods to interrogate vast collections of proteins, to determine pockets of interesting novel families? Metagenomics is transforming our understanding of the microbial world by uncovering enormous numbers of novel proteins. MGnify, one of the largest metagenomics resources, contains ~6 billion unique protein sequences. At the same time, artificial intelligence (AI) methods like AlphaFold and ESMfold can accurately predict protein structures directly from sequence. The AlphaFold database (AFDB) contains models for >200 million UniProt proteins, while the ESM Atlas comprises >600 million models for MGnify proteins, with many more expected soon. A new joint initiative with Christine Orengo’s team based at University College London, we will co-develop scalable strategies for classifying the MGnify protein databases into protein families based on structure and investigate the distribution of novel protein families across taxa and environments.

Your group

The Finn Research Group currently comprises two PhD students and two post doctoral fellows. This team is closely aligned with the Microbiome Informatics team responsible for producing MGnify, the AMR portal and the microbial data in Ensembl. The Finn Research covers a range of different research themes, from computational tool development to deep dives into data driven research topics such as exploring the human skin and gut microbiomes. The tool development takes on a number of different forms, from algorithmic development to the application of emerging AI technologies. These tools are typically designed to work at scale, with a view that many of these will be utilised in the data resources produced by the Microbiome Informatics team.

Your supervisor

You will report directly to Research Group lead, Rob Finn.

Your role

You will co-develop strategies that can deal with the classification of the vast protein database provided by MGnify into protein families based on structure. This will include clustering, functional labelling and developing selection criteria for producing structures. You will help update the current MGnify database with taxonomic information, based on a range of sources from within MGnify. You will also expand the biome information, based on an emerging tool produced within the wider team. Using these pieces of information, you will conduct an investigation looking for correlations between biome and taxonomy and protein family distributions, relating this to functions. Expanding on prior research, you will undertake a specific task aimed at trying to identify bacteriophage encoded bacterial anti-defence systems and use the functional and structural classification to propose potential mode of actions. The research will undertake both methodological approaches (including the adopting of AI-based approaches) as well as data analysis at scale.

You have

* PhD in the biological sciences, computational biology, bioinformatics, computer science or a related field, and proven research experience in a relevant field.
* A strong background and understanding in microbiology and/or metagenomics.
* Understanding of protein classification approaches and the tools that underpin them.
* Research experience dealing with large datasets.
* An eagerness to work in a highly collaborative atmosphere while still being able to work independently and to meet deadlines in a timely manner.
* Strong Python skills, with demonstrable ability to produce well documented and tested software.
* Experience with UNIX/Linux, and HPC or cloud environments
* Motivation to work in an international team on interdisciplinary projects.
* Strong communication and interpersonal skills, with the ability to communicate effectively in English, both verbally and in writing.
* Fluency in English is essential (CEFR C2 minimum or equivalent)

You may also have

* Knowledge about bacterial defence systems and/or bacteriophage anti-defence systems.
* Experience building computational pipelines with Nextflow, Snakemake or similar
* Experience with relational databases (e.g. MySQL, PostgreSQL)
* Experience with software development best practices, including version control (e.g. Git), testing and code review
* Familiarity with AI-assisted coding tools, and an understanding of how to critically evaluate, validate, and improve their outputs
* Desire to help mentor PhD students
* Ability to work independently and collaboratively as part of the research project group, prioritise tasks, and critically evaluate your research outputs.

Benefits and Contract Information

* Financial incentives: depending on circumstances, monthly family/marriage allowance of £291, monthly child allowance of £351 per child. Generous stipend reviewed yearly, pension scheme, death benefit, long-term care, accident-at-work and unemployment insurances
* Hybrid working arrangements
* Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover)
* Generous time off: 30 days annual leave per year, in addition to eight bank holidays
* Relocation package
* Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely)
* Family benefits: On-site nursery, child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances
* Contract duration: This position is a 3 year fixed-term contract
* Salary: Year 1 Stipend at rate of £3,535 per month (Total package will be dependant on family circumstances)
* International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants.
* Diversity and inclusion: At EMBL-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ and individuals from all nationalities.
* Job location: This role is based in Hinxton, near Cambridge, UK. You will be required to relocate if you are based overseas and you will receive a generous relocation package to support you.
* DORA - EMBL is a signatory of DORA and is committed to hiring and training outstanding research, service, and administrative personnel.