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 Computational Biology Group headed by Professor Christine Orengo. The successful applicant will join a pioneering research effort focussed on developing novel AI-based methods for classifying proteins into domain superfamilies and functional families.
About the role
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We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which increase transmissibility of the virus. The project will also be involved in predicting mutations that increase antimicrobial resistance to therapeutic drugs being used against this virus. Another aspect will be to determine the range of hosts that can be infected by the virus. The researcher will develop a platform collating all viral strains, host-viral interaction data and viral-drug interaction data. The researcher will use protein sequence and structure-based features along with protein language models to develop AI based predictors. The final stage will involve developing a diagnostic portal to identify emerging threats.
The work will be in collaboration with Dr. Neeladri Sen and the team of Dr. Su Datt Lam who is based in the National University of Malaysia (UKM).
The predictions will be experimentally validated in the lab of Prof. Wendy Barclay, Imperial College London. Some of the validations will also be performed in the labs of Dr. Muhammad Ashraf Shahidan, Dr. Nurul Hanun Ahmad Raston and Dr. Shazilah Kamaruddin at National University of Malaysia (UKM).
The post also will offer opportunities for exchange visits to UKM in the lab of Dr. Su Datt Lam. This post will also allow outreach activities showcasing the diagnostic portal and engagement with experts in zoonotic surveillance and anti-viral resistance.
This post will be based in the lab of Professor Christine Orengo at UCL.
Interview Date(s) are likely to be scheduled for mid-May 2025.
The salary of the role is advertised between Grade and Grade 8. Please find current salary scales below.
'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 37,332 - 39,980 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.
This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit https://www.ucl.ac.uk/human-resources/conditions-service-research-teaching-and-professional-services-staff for more information.
A job description and person specification can be accessed at the bottom of this page.
If you have any queries about the role, please contact Professor Christine Orengo, c.orengo@ucl.ac.uk.
If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact Biosciences staffing at biosciences.staffing@ucl.ac.uk.
About you
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You must have a PhD in bioinformatics, computational biology, computer science, data science or a related subject area and proven knowledge of python programming, developing machine learning/AI based tools and HPC.
You will be expected to work as part of a tightly integrated team of computational and experimental biologists to produce novel algorithms and workflows to predict the impact of viral mutations on susceptibility and anti-viral resistance.
In addition to developing and conducting the research, you will contribute expertise to the overall research effort in the Orengo group. You will also communicate results as scientific papers in leading journals, and as scientific presentations at national and international conferences.
What we offer
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As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:
41 Days holiday (27 days annual leave, 8 bank holidays and 6 closure days)
Additional 5 days' annual leave purchase scheme
Defined benefit career average revalued earnings pension scheme (CARE)
Cycle to work scheme and season ticket loan
Immigration loan
Relocation scheme for certain posts
On-Site nursery
On-site gym
Enhanced maternity, paternity and adoption pay
Employee assistance programme: Staff Support Service
Discounted medical insurance
Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.
Our commitment to Equality, Diversity and Inclusion
As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.
We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce.
These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.
Our department holds an Athena SWAN Bronze award, in recognition of our commitment to advancing gender equality.
You can read more about our commitment to Equality, Diversity and Inclusion here: https://www.ucl.ac.uk/equality-diversity-inclusion/
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