At a Glance
- Tasks: Design and apply advanced machine learning techniques to DNA and genetic data.
- Company: Join Relation, a pioneering TechBio company transforming medicine through innovative technology.
- Benefits: Competitive salary, inclusive culture, and the chance to impact patient lives.
- Why this job: Be at the forefront of ML for genomics and contribute to groundbreaking research.
- Qualifications: PhD in machine learning or related field, with experience in biological sequences.
- Other info: Dynamic team environment with opportunities for professional growth and collaboration.
The predicted salary is between 60000 - 80000 £ per year.
About Relation
Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis program. By combining our cutting-edge ML capabilities with GSK’s deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients.
We are rapidly scaling our technology and discovery teams, offering a unique opportunity to join one of the most innovative TechBio companies. Be part of our dynamic, interdisciplinary teams, collaborating closely to redefine the boundaries of possibility in drug discovery. Our state-of-the-art wet and dry laboratories, located in the heart of London, provide an exceptional environment to foster interdisciplinarity and turn groundbreaking ideas into impactful therapies for patients. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the grounds of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. We cultivate innovation through collaboration, empowering every team member to do their best work and reach their highest potential. By joining Relation, you will become part of an exceptionally talented team with extraordinary leverage to advance the field of drug discovery. Your work will shape our culture, strategic direction and, most importantly, impact patients’ lives.
The Opportunity
As a Machine Learning Scientist within the Rosalind team, you will design and apply advanced machine learning techniques to DNA and genetic data. This role is ideal for someone with a strong machine learning background and an interest in genetics. Your work will directly contribute to uncovering non-trivial associations between genetic variants and diseases, ultimately advancing therapeutic discovery.
The Team You Will Join
The Rosalind team aims to extract useful insights through representations of DNA, whether related to variants, genes or the regulatory mechanisms in between. Sitting at the forefront of ML for genomics, the team develops models that help uncover meaningful biological signals from DNA and turn them into foundations for our target discovery pipelines. The team also has a strong track record of publishing at major ML venues, including winning a Best Paper award for PatchDNA at the NeurIPS AI4D3 workshop and publishing recently in the main conference track at ICLR.
Your Responsibilities
- Develop and apply sequence modelling machine learning techniques to DNA sequences
- Train, fine-tune and evaluate DNA sequence models for tasks including variant interpretation, gene discovery and regulatory modelling
- Collaborate with computational and experimental scientists to generate and validate ML-driven hypotheses
- Leverage large-scale external and internal datasets to build and adapt models for disease-focused applications
- Design robust evaluations to measure model quality, biological relevance and translational value
- Contribute to scientific innovation by applying the latest advances in machine learning and genomics.
Professionally, You Have
- A PhD in machine learning, computational biology, or a related field, or equivalent industrial experience
- Demonstrated experience applying machine learning techniques to biological sequences or text
- Proficiency in Python and at least one ML platform (e.g. PyTorch, TensorFlow)
- Flexibility and the ability to tackle new challenges at the intersection of biology and machine learning.
Desirable Knowledge or Experience
- Experience applying machine learning to biological sequences, including DNA or proteins
- Strong understanding of transformers and their applications in biomedical research
- Knowledge of lab-in-the-loop frameworks and integration of ML techniques with experimental data.
Personally, You Are
- An inclusive leader and team player
- A clear communicator
- Driven by impact
- Humble and eager to learn
- Motivated and curious
- Passionate about making a difference in patients’ lives
Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to bring transformative medicines to patients. Together, we’re not just doing research; we’re setting new standards in the field of machine learning and genetics. The patient is waiting!
Machine Learning Scientist – Sequence Modelling employer: Relation Therapeutics Limited
Contact Detail:
Relation Therapeutics Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Scientist – Sequence Modelling
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Relation or similar companies. Use LinkedIn to connect and engage with them; you never know who might help you land that interview.
✨Tip Number 2
Prepare for technical interviews by brushing up on your machine learning skills. Practice coding challenges and be ready to discuss your past projects in detail. Show them how your experience aligns with their mission!
✨Tip Number 3
Don’t just apply and wait! Follow up on your applications through our website. A quick message expressing your enthusiasm can make a big difference and show you're genuinely interested in the role.
✨Tip Number 4
Be yourself during interviews! Relation values diversity and inclusion, so let your personality shine through. Share your passion for machine learning and how it can impact patients' lives—this is what they want to hear!
We think you need these skills to ace Machine Learning Scientist – Sequence Modelling
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that are most relevant to the Machine Learning Scientist role. Highlight your machine learning projects, especially those related to genetics or biological sequences, to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your passion for the role and the impact you want to make. Share specific examples of how your work aligns with our mission at Relation and why you're excited about the opportunity.
Showcase Your Technical Skills: We love seeing proficiency in Python and ML platforms like PyTorch or TensorFlow. Be sure to mention any relevant projects or experiences that demonstrate your technical prowess in machine learning and genomics.
Apply Through Our Website: To ensure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Relation Therapeutics Limited
✨Know Your Stuff
Make sure you brush up on your machine learning techniques, especially those related to sequence modelling and genetics. Be ready to discuss your previous projects and how you've applied ML to biological sequences. This will show that you're not just familiar with the theory but have practical experience too.
✨Show Your Collaborative Spirit
Since this role involves working closely with both computational and experimental scientists, be prepared to talk about your teamwork experiences. Highlight any interdisciplinary projects you've been part of and how you contributed to achieving common goals. This will demonstrate that you can thrive in a collaborative environment.
✨Ask Smart Questions
Prepare insightful questions about the company's current projects, especially those related to their collaboration with GSK or their internal osteoporosis programme. This shows your genuine interest in their work and helps you understand how you can contribute to their mission of advancing drug discovery.
✨Be Ready to Discuss Evaluation Metrics
Since you'll be designing robust evaluations for model quality and biological relevance, be prepared to discuss how you measure success in your projects. Talk about specific metrics you've used in the past and how they relate to the impact of your work on patient outcomes. This will highlight your analytical skills and focus on real-world applications.