At a Glance
- Tasks: Lead innovative research using Large Language Models to revolutionise drug discovery.
- Company: Join a pioneering team at Isomorphic Labs, where creativity meets cutting-edge science.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative and inclusive culture with a focus on interdisciplinary teamwork.
- Why this job: Make a real impact in healthcare by applying AI to solve complex scientific challenges.
- Qualifications: PhD or equivalent experience in machine learning or related fields; strong LLM expertise required.
The predicted salary is between 70000 - 90000 € per year.
Requirements
- PhD or equivalent practical experience in a technical field
- Highly specialized LLM builder with a passion for, and strong experience in, applying LLMs to novel problem spaces
- Deep understanding and experience of model architectures, training methods, and techniques for application of LLMs, including deployment for bespoke use cases and applications
- Established experience in post‑training, reasoning, test‑time scaling, tool‑use, alignment, agents, LLM research, as well as reinforcement learning and fine‑tuning
- Strong knowledge of linear algebra, calculus and statistics
- Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas
- Depending on your experience: project supervision, leadership, or management
- Strong knowledge of LLM landscape today, and likely developments for the near future
- Experience working with real‑world datasets
- (Desirable) PhD in machine learning or computer science
- (Desirable) Relevant research experience to the position such as postdoctoral roles, a proven track record of publications, or contributions to machine learning codebases
- (Desirable) A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery
- (Desirable) Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software
- (Desirable) Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real‑world scientific challenges
- (Desirable) Experience with multi‑parameter optimization
- (Desirable) Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real‑world applied RL
What the job involves
- As a Research Scientist focused on the application of Large Language Models (LLMs), you will play an exciting role in bringing cutting‑edge technologies to bear across our research areas to transform the drug discovery world as we know it
- Working in a highly creative, fast‑paced and interdisciplinary environment, you will be partnering with leading research scientists and engineers to conceive, design, and develop cutting‑edge LLM applications that help to unlock new modelling capabilities and predictive power which will be critical to the organisation’s success
- You will draw upon your existing deep understanding and experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems
- You will both partner with teams across our existing research areas and create and lead standalone projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems through the application of LLMs
- You will be instrumental in leading machine‑learning based research projects, building the models and the algorithms that will power our platform to drive us close to achieving our ambitious mission to one day solve all disease with the help of AI
- Contribute to core research in machine learning by pushing the boundaries of Large Language Models in their application to the world of drug discovery
- Develop and refine LLM‑driven approaches for multiple use cases across our research areas, using your extensive knowledge of the field to modify and apply models and explore their capabilities when applied to complex biological and medical challenges
- Identify and create novel ML techniques and the required data to train and apply models
- Analyse and tune experimental results to inform future experimental directions
- Implement and scale training and inference engineering frameworks
- Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines
- Iterate collaboratively with scientists and domain experts, sharing your own domain experience
- Suggest and engage in team collaborations to meet ambitious research goals
- Depending on your experience: Provide technical mentorship and guidance to the ML research community, advising on projects and shaping our research roadmap based on your deep technical expertise
- Provide developmental support to other ML research scientists
- Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high‑priority modelling problems
- Cultivate a diverse and inclusive research culture
Research Scientist (Applied LLMs) in London employer: Deepstreamtech
Isomorphic Labs is an exceptional employer for Research Scientists, particularly those passionate about applying Large Language Models to transformative drug discovery challenges. With a vibrant and interdisciplinary work culture, employees benefit from collaborative projects, technical mentorship opportunities, and the chance to contribute to groundbreaking research that aims to solve complex medical problems. Located in a dynamic environment, the company fosters innovation and personal growth, making it an ideal place for those seeking meaningful and impactful careers in machine learning and computational biology.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist (Applied LLMs) in London
✨Tip Number 1
Network like a pro! Reach out to fellow researchers, attend conferences, and join online forums. The more connections we make, the better our chances of landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects and research. We want to see how you've applied LLMs in real-world scenarios, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We should be ready to discuss our experience with ML frameworks and model architectures in detail.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Research Scientist (Applied LLMs) in London
Some tips for your application 🫡
Show Off Your Passion:When writing your application, let your enthusiasm for LLMs and their applications shine through. We want to see how your passion aligns with our mission in drug discovery!
Tailor Your Experience:Make sure to highlight your relevant experience with LLMs, model architectures, and any specific projects you've worked on. We love seeing how your background fits into the exciting work we do at StudySmarter.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so make sure your skills and experiences are easy to understand. Remember, less is often more!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get you into our system quickly. We can’t wait to hear from you!
How to prepare for a job interview at Deepstreamtech
✨Know Your LLMs Inside Out
Make sure you have a deep understanding of Large Language Models and their applications. Brush up on the latest advancements in the field, especially those relevant to drug discovery. Be ready to discuss specific projects or research you've done that showcases your expertise.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency with ML frameworks like JAX, PyTorch, or TensorFlow. Have examples ready that highlight your experience with model architectures, training methods, and real-world datasets. This is your chance to shine, so don’t hold back!
✨Collaborative Spirit is Key
Since the role involves working with interdisciplinary teams, be prepared to discuss how you've successfully collaborated with scientists from different fields. Share examples of how you’ve contributed to team projects and how you can bring diverse perspectives together.
✨Be Ready for Problem-Solving
Expect to tackle some complex computational biology or chemistry problems during the interview. Think through potential challenges you might face in the role and how you would approach solving them. This will show your analytical skills and readiness for the job.
