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GSK.ai Fellow, Crick-GSK Prosperity Partnership in Systems Chemical Biology (3-Year appointment)

The Crick-GSK LinkLabs is a well-established, strategic partnership in chemical biology which has recently been awarded a 5-year EPSRC Prosperity Partnership to develop cutting edge technology for simultaneous identification of disease-associated proteins and functional chemical probes. Our platform is using reactive fragments and chemical proteomics to generate large-scale, full-matrix datasets which will be used to train machine learning models of ligand-protein interactions. The team is also exploiting high-content approaches, including cell imaging, global proteomics and metabolomics, to map the biological responses of target perturbations. This ambitious, long-term research programme is driven by a high calibre, multi-disciplinary team, drawing on the combined expertise of GSK and The Francis Crick Institute. With successful implementation of our experimental workflows, we are now pleased to announce a GSK.ai Fellowship aligned to this long-term partnership.

Roles and Responsibilities

Sponsored by GSK.ai, this role is for a 3-year research Fellowship working as part of an integrated team, based in London between GSK’s Kings Cross AI hub and The Francis Crick Institute. The successful candidate will be expected to influence the experimental direction of the programme through the development of predictive models of ligand-target interactions and relating these ligand-target associations to complex cellular responses. The role will require strong learning agility and flexibility to work on a host of biological systems, closely partnered with chemists, biologists and bioinformaticians.

Applicant profile

This position is expected to appeal to data scientists with interests in the scientific domains relevant to our partnership (i.e. chemistry, structural biology, (chemical)proteomics and/or cell biology). The successful applicant can expect excellent onward training in early-stage drug discovery as well as the opportunity to collaborate with experts working in other disciplines, including structural biology, proteomics, gene editing, molecular biology and medicinal/synthetic chemistry.

Please use your covering letter to highlight how you fit the applicant profile and meet the skills and competencies for the role. Your covering letter, along with your CV, will be used to assess your application.

We’re combining the power of genetic and genomic insights into what causes disease, with the speed and scale of artificial intelligence and machine learning (AI/ML) to make better predictions about who a treatment might work for, and why. We believe this powerful combination of data and technology holds the key to fundamentally transforming medical discovery for the better, improving R&D success rates and shaping how even the most challenging diseases, like neurological conditions and cancer, can be both prevented and treated.

In 2021 we delivered four major product approvals: Cabenuva for HIV, Jemperli for endometrial cancer, Xevudy for COVID-19 and Apretude, our new long-acting medicine for HIV prevention.

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Our approach to R&D

In this role you will

• Work flexibly across the Crick-GSK Prosperity Partnership to drive the design and implementation of methods/models for expanding the ligandable proteome and relating complex biological signatures to small molecule (and genetic) perturbations.
• Foster integrated working between GSK.ai and the Prosperity Partnership teams, contributing to a culture of scientific excellence.
• Guide and mentor experimentalists in the application (and limitations) of computational models.
• Engage with senior stakeholders, external advisors and our wider network of external collaborators.
• Disseminate research outcomes through publications in high-impact journals and presentations at prestigious conferences.

Closing Date for Applications: 24th May (COB)

Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

During the course of your application you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process. If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements, please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.

• LI-GSK

Why you?

Qualifications & Skills:

We are looking for professionals with these required skills to achieve our goals:

• PhD/DPhil in computational science, or life sciences with a significant computational component.
• First class or 2:1 degree (or equivalent) in computer science, chemistry, biochemistry or STEM discipline.
• Expert understanding of at least one programming language, ideally Python.
• Experience of at least one deep learning framework such Scikit-learn, Keras, Tensorflow or PyTorch (preferred).
• Experience of carrying out independent research
• Evidence of strong problem-solving & high learning agility
• Self-starting, proactive and ability to manage multiple tasks simultaneously.
• Experience of effective collaborative working in an integrated setting, ideally with laboratory-based scientists.
• Proven ability to critically analyse, assimilate, and communicate complex scientific data.
• Commitment to personal professional development and a track record of consistent high performance.

Preferred Qualifications & Skills:

If you have the following characteristics, it would be a plus:

• Experience of developing and applying machine learning-based methodologies.
• A history of publishing research in high-impact journals.

• Experience with molecular structure handling and manipulation (e.g. using RDKit or similar for chemical structures, BioPython/Biopandas or similar for protein structure).

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We’re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.

As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to neurodiversity, race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class*(*US only).

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us on [email protected] or 0808 234 4391. Please note should your enquiry not relate to adjustments, we will not be able to support you through these channels

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