About us
Biosciences is one of the world’s foremost centres for research and teaching in the biological sciences and one of the largest Divisions within UCL, undertaking a significant amount of research and teaching. The Division has a diverse portfolio addressing all areas of biology from protein interactions to cell function, organism development, genetics, population studies and the environment. Computational modelling approaches are frequently used alongside experimental research programmes and much of our research crosses traditional boundaries, including the relationship of biodiversity to the health of the planet. Activity is underpinned by high calibre science technology platforms and state of the art equipment. Educational activity includes a range of undergraduate programmes, an expanding number of Masters Programmes and a substantial number of postgraduate research students.
This is an exciting opportunity to join the Orengo Group within the UCL Research Department of Structural and Molecular Biology to work on an interdisciplinary BBSRC funded project involving 4 world-leading research groups (Christine Orengo UCL, Rob Finn, European Bioinformatics Institute, Florian Hollfelder, University of Cambridge, Marko Hyuninen, University of Cambridge). The appointed researcher will be part of a Horizon Europe project on marine metagenomics and bioremediation.
About the role
The researcher in the Orengo Group will be involved in developing novel AI/machine learning methods for predicting protein functions. Our project will identify new plastic-degrading enzymes and other enzymes linked to bioremediation taking advantage of the vast amount of metagenomic sequencing data as input for the methods. We will also exploit predicted protein structural data to expand the feature set. Collaborations with the experimental team in Cambridge will provide validation of the computational predictions via ultrahigh throughput screening in microfluidic droplets.
The Orengo group already have considerable expertise in protein function prediction using sequence data. Our methods have been highly ranked in all rounds of the Critical Assessment of Functional Annotations (CAFA). In this project we will take these approaches forward using deep learning strategies and exploiting protein structure data.
This role is an open-ended contract, funded for 3 years in the first instance.
Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £35,702 - £37,548 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.
Please note that appointment at Senior Research Fellow level is dependent on the extent and relevance of postdoctoral experience and experience of supervising other researchers, and salary is limited to Grade 8 spinal point 37 (£48,614 per annum).
You should hold a PhD in a relevant field (computer science, bioinformatics or computational biology) or be about to submit a thesis. Advanced programming skills and experience of Python, machine learning, databases and SQL, Linux or other unix-like operating systems are all essential for the role. Previous experience in bioinformatics research or computer science is highly desirable, especially in machine learning and deep learning. Knowledge of protein structures and functions is also desirable.
You will be expected to produce novel algorithms to detect plastic degrading enzymes in metagenome samples. In addition to developing and conducting the research, you will communicate results as scientific papers and in scientific presentations at local, national, and international conferences.
See application form details on:
www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?nPostingId=5261&nPostingTargetId=10978&id=Q1KFK026203F3VBQBLO8M8M07&LG=UK&languageSelect=UK&mask=ext