Principal Research Scientist – In Silico Biologics Design

Job title:

Principal Research Scientist – In Silico Biologics Design

Company

Lifelancer

Job description

The Principal Scientist In Silico Biologics Design will provide world class expertise in machine learning to drive the establishment of robust in silico methodologies that integrates computational predictions with empirical laboratory data to revolutionise the design of our class-leading T-cell receptor (TCR) drugs. Using our wealth of structural data, combined with further in-house and public domain data sets, the successful applicant will develop ML algorithms to impact the design of future drugs. This is an exciting technology-focussed role so innovation, execution and collaboration are key factors for success. Working closely with the In Silico and automation teams within Protein Engineering, you will provide scientific and technical leadership relating to machine learning that will ultimately result in further progression of our growing pipeline of first-in-class drugs to benefit patients. With our successful launch in 2022, of the world’s first TCR based medicine, KIMMTRAK, which is also the first launched treatment for any solid tumour, you will be joining us at the most exciting time in our history, and be part of a team that values innovation, trust and collaboration.KEY RESPONSIBILITIES

• To develop and assess advanced machine learning (ML) models for novel antibody and TCR drug candidate optimisation and, looking to impact de novo drug design in the future

• Utilise our extensive in-house structural and specificity data sets to extract further value

• Work with colleagues across Research to identify training data from the public domain and help shape the development of our in-house data sets to support the optimisation of ML algorithms

• Drive the establishment of virtual screening tools including:
• Protein structure prediction
• Affinity prediction
• Peptide human leukocyte antigen (pHLA) specificity prediction
• Developability prediction

• Assist with TCR library design for multifactorial lead optimisation

• Work with interdisciplinary teams across structural biology, next-generation sequencing (NGS), and bioinformatics and data science to integrate machine learning into TCR discovery and optimisation.

• Work with scientists to validate and integrate new methodologies into existing architecture.

• Promote utilisation of ML algorithms among colleagues and mentor and train others in their deployment

• Present research outcomes at all levels, including Protein Engineering lab meetings, Research leadership team meetings, other governance meetings and at external conferences

PERSON SPECIFICATIONExperience knowledgeEssential

• Demonstrated ability to build and evaluate machine learning models

• At least 8 years of experience in antibody, TCR or biologics design, evidenced by a strong publication record.

• Proficiency with protein ML models such as AlphaFold, ESMFold, RFdiffusion, MPNN

• Advanced Python programming skills, focusing on data science and machine learning.

• Managed sizeable research projects, understanding the wider implications of project outcomes and strategic objectives.

• Demonstrates effective coaching skills and brings vision and strategy to life for others.

• Exceptional communication skills.

• Demonstrated ability to build and sustain networks and external collaboration with scientific leaders in the field.

Desirable

• Expertise in structural biology and modelling

• Experience in NGS analysis.

• Experience with biologics data management software including Genedata and in handling and integrating large-scale biological datasets from different sources.

• Familiarity with deploying and managing computational workflows on cloud platforms (e.g. AWS)

Education qualifications

• PhD in Computational Biology, Computational Chemistry, Bioinformatics, or related discipline.

Lifelancer ( ) is a talent-hiring platform in Life Sciences, Pharma and IT. The platform connects talent with opportunities in pharma, biotech, health sciences, healthtech, data science and IT domains.Please use the below Lifelancer link for job application and quicker response.

Expected salary

Location

Oxford

Job date

Thu, 11 Jul 2024 22:12:19 GMT

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