Relation Therapeutics is a TechBio company pioneering recommender systems biology to bring forward new drugs for patients with diseases of high unmet need.
Relation are combining single-cell profiling, human genetics, functional genomics, and end-to-end machine learning to better understand human biology. The company’s ultimate goal is to transform how drug discovery & development is conducted, leading to new medicines for diseases where there is a tremendous need.
Relation is using graph-based recommender system technologies to reveal causal relationships in diseases that until now have been impossible to understand using traditional technologies. Ultimately, Relation’s platform will be capable of identifying which areas of biology to focus on and greatly accelerates discovery research efforts for diseases that have not previously been widely researched.
As a Machine Learning Scientist at Relation, you will work in an interdisciplinary team (including Data Scientists, Data Engineers and experimental scientists) to deliver our strategic priorities in machine learning and to help build our proprietary technologies. This includes contributing to the design and execution of machine learning projects using the latest methods and engineering best practices, combining typical ML methods with modern graph and NLP-based machine learning architectures such as graph convolutional neural networks, graph attention networks and transformers. You will have experience of working in high-performing ML research groups. You will work within our engineering standards and ways of working. You will conduct basic ML research (in partnership with senior group members) and continue to engage with the external community, through papers at the major ML conferences (including NeurIPS, ICML, ICLR and AISTATS) and broader engagement activities including technical blogs etc. As the company is rapidly growing, there may be opportunities to manage a team.
By joining Relation, you will be part of an exceptionally talented team, learn a broad range of skills within and outside your area of expertise, help us shape our culture and strategic direction and ultimately, make a positive impact in patients lives.
● Work efficiently in a team of 3-10 to optimally deliver projects using the latest ML methods and modern engineering best practices.
● Work closely with bioinformaticians and experimental scientists to review and translate ML
methods into meaningful insights for drug development and computational biology.
● Contribute ideas and provide creative input to machine learning projects.
● Adhere to Relation’s AI standards and ways of working.
● Continue to actively engage in ML research with and through the broader ML research community. Publish papers at the major ML conferences and contribute technical blogs.
● Remain at the cutting edge of ML research, especially in a chosen subfield (e.g. probabilistic / causal ML, graph NNs, NLP etc.).
Professionally, you have :
● A BSc in machine learning, computer science or other quantitative discipline; or equivalent
industrial experience and preferably a PhD in machine learning, computer science or other quantitative discipline;
● Deep expertise in contemporary AI/ML methods and topics, including computer vision, NLP, structured data, probabilistic / causal ML, normalizing flows etc.
● Experience with biological / health / chemical data a bonus
● A proven track record of excellence in machine learning research including conference papers / presentations at NeurIPS / ICML / ICLR
● Track record of collaborating successfully with AI engineering teams to deliver complex modelling projects
● Experience as a proficient Python developer (2 - 5 years of industrial experience); must be familiar with modern software engineering practices and the use of modern collaborative tools (e.g. GitHub, Slack, Jira, Trello etc.)
● Experience in at least one major machine learning platform; preferably PyTorch (although TensorFlow is acceptable)
Personally, you are:
● A great team player
● A clear communicator
● Driven by impact
● Humble and hungry to learn
● Motivated and curious
● Passionate about making a difference in patients’ lives
To apply for this position please email email@example.com with a cover note and CV.
Relation Therapeutics is a committed equal opportunities employer.