Project Opportunity within OMass Therapeutics Bioinformatics Team: Machine learning based drug target identification
Project duration: 12 months
OMass Therapeutics is an early-stage drug discovery company, applying its unique OdyssION™ technology platform, which comprises novel biochemistry techniques, next-generation native mass spectrometry, and custom chemistry, to discover small molecule therapeutics for rare diseases and immunological conditions.
The company was founded by Professor Dame Carol Robinson to leverage her pioneering work in native mass spectrometry, in studies of dynamic protein assemblies, to characterise challenging drug targets including membrane proteins. The high resolution of our biophysical platform offers an unprecedented advantage in the detection of drug leads. The company vision is to build an integrated drug discovery company, with the ambition to develop and ultimately commercialise our products.
Headquartered in Oxford, UK, OMass has raised over $150M (£119M) from a top-tier international investor syndicate, including Syncona, Oxford Science Enterprises, GV, Northpond Ventures, and Sanofi Ventures. This is an excellent time to join our dynamic growing company.
OMass bioinformatics team is implementing a data-driven and AI-enabled approach to identify novel targets for drug development using its proprietary platform. We invite talented applicants for a one-year project opportunity to work within the bioinformatics department. We offer a cutting-edge project to apply your skills at the intersection of machine learning/deep learning and network biology.
The successful candidate will learn about data-driven approach of identifying novel drug targets that can change the lives of patients with unmet needs. The role is based remotely with the visiting opportunity to our Oxford site.
Applications to be received by 15th August 2022
Essential Experience, Skills and Qualities
• Msc or equivalent in Machine Learning, Computer science, Computational biology, bioinformatics
• Proficient programming skills in R or Python
• Ability to build and apply Machine Learning/ Deep learning models on graph databases.
• Practical with Linux and Bash scripting.
• Comfortable using Git/GitLab.
• Responsible and focused approach to independent and collaborative work, with the ability to prioritise and deliver high quality work to deadlines.
• Innovative and ambitious mindset, with an inquisitive and agile approach to problem-solving and overcoming technical challenges; motivated to continuously learn and take on challenges in the pursuit of delivering novel therapeutics.
• Caring and inclusive; respectful and receptive to others’ diverse ideas, experience and perspectives, and enjoys working collaboratively with others as a team.
• Excellent communication skills, both written and verbal.
Preferred Experience and Skills
• Familiarity or interest in learning Neo4j/Cypher and knowledge graphs.
• Familiarity or interest in learning BigQuery/GraphQL.
• Basic understanding of biology, genetics
• Collect and preparing data from relevant sources using API portal (R, Python, GraphQL).
• Designing a graph model and transforming data tables into a graph in Neo4J.
• Developing ML/DL models for classification and prediction using embeddings of the knowledge networks.
• Contributing to preparation of a protentional manuscript.
• Promote and adhere to OMass’ values of being Ambitious, Responsible, Innovative, Focused, Caring and Collaborative.
Job Type: Full-time, 12 month project
OMass Therapeutics values diversity and is committed to equality of opportunity, we also have full responsibility to ensure that all employees are eligible to work and live in the UK.