Summary
Based on a year of strong growth, further validation of the core AI technologies and recent acquisition of laboratory space, we are looking to expand our bioinformatics capabilities to support the company’s Drug Discovery activities. We are keen to hear from experienced Bioinformaticians, with a proven track record of integrating and analysing Omics datasets, to join the growing Biomedical Informatics department.
Company
BenevolentAI is the global leader in the development and application of AI for scientific innovation and one of the world’s top five private AI companies. It is transforming the process of scientific discovery by enabling previously unimaginable scientific advances in the accelerated development of new medicines.
BenevolentAI has built a leading position in artificial intelligence by developing technologies that deliver previously unimaginable scientific advances, rapidly accelerate scientific innovation and completely disrupt traditional methods of scientific discovery. The technology has been validated in drug discovery, specifically, in the most challenging field of human biology: the identification of new disease targets.
By amplifying a researcher’s ability to grasp an entire corpus of data and iterate the scientific method at exponentially faster rates, BenevolentAI brings highly advanced tools to traditional R&D programmes enabling artificial intelligence to be applied to the scientific discovery process.
Job Overview & Key responsibilities:
- You will have a passion for processing, analysing and integrating ‘Omics (genomics, epigenomics, transcriptomics and proteomics) datasets for biological insights that lead to testable hypotheses relevant to Drug Discovery and Clinical Development programmes undertaken by BenevolentAI.
- As a member of the Biomedical Informatics department you will be responsible defining research objectives and disseminating the latest Omics, Bioinformatics and Computational Biology research trends and developments throughout the company.
- You will be working as member of a cross-functional team (Informatics, Engineering, AI, Drug Discovery and Product).
- You will develop omics-focused tools and workflows that enable internal access to high quality biomedical data.
Requirements & Qualifications:
- A PhD in bioinformatics, computational biology or related field of research.
- 3 years experience in developing software, databases and undertaking statistical analysis to support the Drug Discovery or Clinical Development processes.
- Expert at interpreting and Omics datasets and providing necessary statistical analysis to support the Drug Discovery or Clinical Development.
- Expert programmer in at least one language. We have a preference for Python, but are also interested in Java and R. Candidates should also be familiar with the language packages that support Bioinformatic, Data Science and Machine Learning activities.
- Proven track record of processing and deriving novel insights from Omics resources, such as Gene Expression Atlas, GEO, Array Express, TCGA and LINCs or Clinical databases
- Experience of integrating ‘omics data with broader range of biomedical resources to support drug discovery activities such as ChEMBL, ENSEMBL, PubChem, UniProt, PDB.
- Experience with using biomolecular network based approaches to interpret omics data and aid drug discovery or clinical biomarker development e.g. causal reasoning and functional module detection.
- Experience in processing and analysing transcriptomics datasets using Bioconductor packages (e.g. DSeq2, edgeR, Limma) and other related toolkits (e.g STAR, Salmon, Kallisto, WGCNA).
- Experience in using technologies we like, which includes: include Neo4j, GraphQL, ElasticSearch, MySQL, MongoDB, Spark, GitLab, Kubernetes, AWS, KNIME, Jupyter.
- A strong external network of contacts across industry and academia to engage in ideas and knowledge share.
- Excellent communicator, both verbal and written, with ability to influence at all levels and in across departments.
Desirable Requirements
- Experience in designing Omics focused experiments, that actively support ongoing research projects.
- Experience with patient-level clinical data: observational or interventional cohorts, clinical trials or real-world data.
- Familiar with of chemical structure representations and experience in using cheminformatics libraries (e.g. RDKit)
- Experience with agile based software development practices
Department: Biomedical Informatics
City: London
Type: Permanent
Salary & Benefits
The company offers competitive salaries depending on experience as well as annual bonus, share options scheme, life insurance, health cash plan, pension plan, cycle to work scheme and perks (Fresh fruits, breakfast, coffee, outings and parties …)
Apply now!
If you’d like to join us, please email your CV and a covering letter to our team here: benevolentai.workable.com/j/AE891027E1
Find more exciting opportunities at: benevolent.ai/join-our-team/
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Requirements & Qualifications:
- A PhD in bioinformatics, computational biology or related field of research.
- 3 years experience in developing software, databases and undertaking statistical analysis to support the Drug Discovery or Clinical Development processes.
- Expert at interpreting and Omics datasets and providing necessary statistical analysis to support the Drug Discovery or Clinical Development.
- Expert programmer in at least one language. We have a preference for Python, but are also interested in Java and R. Candidates should also be familiar with the language packages that support Bioinformatic, Data Science and Machine Learning activities.
- Proven track record of processing and deriving novel insights from Omics resources, such as Gene Expression Atlas, GEO, Array Express, TCGA and LINCs or Clinical databases
- Experience of integrating ‘omics data with broader range of biomedical resources to support drug discovery activities such as ChEMBL, ENSEMBL, PubChem, UniProt, PDB.
- Experience with using biomolecular network based approaches to interpret omics data and aid drug discovery or clinical biomarker development e.g. causal reasoning and functional module detection.
- Experience in processing and analysing transcriptomics datasets using Bioconductor packages (e.g. DSeq2, edgeR, Limma) and other related toolkits (e.g STAR, Salmon, Kallisto, WGCNA).
- Experience in using technologies we like, which includes: include Neo4j, GraphQL, ElasticSearch, MySQL, MongoDB, Spark, GitLab, Kubernetes, AWS, KNIME, Jupyter.
- A strong external network of contacts across industry and academia to engage in ideas and knowledge share.
- Excellent communicator, both verbal and written, with ability to influence at all levels and in across department
If you’d like to join us, please email your CV and a covering letter to our team here: benevolentai.workable.com/j/AE891027E1