We are keen to hear from experienced bioinformaticians who are driven to build technology and products to accelerate drug discovery. You will work as part of a cross-functional team to tackle problems across the drug discovery process including target identification, molecular design and drug repurposing. You will bring your expert knowledge of using multi-modal biomedical data coupled with strong data science skills to derive insights and build workflows that are used by drug discovery teams to augment their scientific decision making. You will be part of the wider Informatics team who are the domain experts for biological, chemical, and clinical data at BAI and its application to enable drug discovery in our technology platform.
Responsibilities
- Lead the development of scalable computational approaches and workflows to address problems across the drug discovery process including disease mechanism recommendation, ranking targets with respect to their biological importance, and repurposing existing drugs for new indications.
- Work within a multidisciplinary team of data scientists, machine learning specialists and software engineers. to develop user facing products for drug discovery scientists that incorporates insights from multi-modal biomedical data
- Contribute to BAI and partner drug discovery programmes through the application of the Benevolent PlatformTM in collaboration with drug discovery biologists, chemists, and clinicians.
- Collaborate and communicate effectively across product, technology, and drug discovery scientific disciplines and functions to achieve BenevolentAI strategic goals.
- Contribute towards BenevolentAI’s ongoing and future external collaboration activities
We are looking for:
- A PhD, or equivalent industrial experience in bioinformatics, statistics or other computational subject with application to biology.
- Proficient programmer in at least one language (preferably python) for use in data analysis, automation and testing.
- Experience working with and integrating a wide range of biomedical data types and resources that include databases such as OMIM, Reactome, Chembl; technologies such as text mining/NLP; and analysis of primary datasets such as genomics/genetics, protein structure, chemistry, or clinical data.
- Experience, preferably in or with industry, in developing and applying computational methods to derive novel insights from data to support one of more parts of the drug discovery process (e.g. target identification, molecular design, patient stratification)
- Familiarity with database and graph technologies such as MySQL and Neo4j.
- Knowledge and experience of product/tool development
- Familiarity with modern software development paradigms, including containerisation with Docker, GitOps, and cloud computing
- Excellent communicator, both verbal and written, with an ability to share knowledge and ideas between scientific and engineering disciplines.