Research Scientist

Posted 4 Days Ago
Be an Early Applicant
Oxford, Oxfordshire, England, GBR
In-Office
Entry level
Artificial Intelligence • Healthtech • Social Impact • Biotech
The Role
Develops machine learning and physics-based methods for biomolecule and enzyme design, including generative models, molecular simulations, and predictive design-build-test workflows. The role connects research innovations to experimental campaigns, develops evaluations and training algorithms, publishes findings, mentors researchers, and collaborates with experimental, scientific, data, and infrastructure teams.
Summary Generated by Built In

Job Summary

At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges. 

We are looking for visionary Research Scientists in the Molecular Simulations and Design team who balance machine learning innovation with a mission-driven bias toward execution. 

Molecular Simulations and Design accelerates the design of biomolecules, with an initial focus on enzymes, by combining generative models, physical simulation, and learning from experimental data. You will push the frontier where these three meet. You will have the unique opportunity to translate your research innovations directly to experimental campaigns with a rapidly accelerating feedback cycle. We are particularly excited about physics-based methods working together with generative models to lead to generalizable and robust predictions of experimental outcomes and designs. 

  • Innovative research in new methodologies e.g.,: Boltzmann samplers, long-timestep molecular dynamics, machine learned interatomic potentials, generative models (including flow matching, diffusion). Full-stack research, from pre-training to fine-tuning to design-build-test loops. 
  • Key Challenge: Predictive simulation-based workflows, accelerated by machine learning. Merging physics and machine learning for robust generalization. Robust evaluations that translate to downstream impact on campaigns. Research innovations that go beyond performance on evals and have measurable acceleration of experimental campaigns.  
  • Ideal Background: PhD in a relevant field with a track record of excellence at the intersection of machine learning, biomolecules and simulations. Expertise building simulation-based pipelines to predict experimental outcomes and using machine learning to accelerate those pipelines. Experience with production grade pipelines for small molecules, biomolecules design and simulations. Agentic engineering skills and ability to build and validate end-to-end machine learning pipelines and in-silico design-build-test loops. Ability to ship at a high velocity. 

Requirements

Responsibilities 

You will be expected to: 

  • Innovate & Lead: Conceptualize and develop original evals, training algorithms and fine-tuning recipes and connect them to ongoing design-build-test-loops 
  • End-to-end impact: Translate your work to experimental campaigns with a rapid feedback cycle. 
  • Publish & Present: Contribute to the global AI community through mentoring PhD students, co-authoring high-impact publications (NeurIPS, ICML, ICLR, etc.) and technical reports. 
  • Collaborate: Partner with cross-disciplinary squads of experimentalists, scientific domain experts, data domain experts and infrastructure to quickly move innovation to impact. 

Qualifications & Skills 

  • PhD in Machine Learning, AI, Computer Science, or a related quantitative field (Physics, Math, Computational Biology), or equivalent experience. 
  • Research Excellence: A proven track record of impactful research demonstrated by e.g. publications in top-tier AI venues or scientific journals. 
  • Technical Mastery: Deep expertise in deep learning frameworks and the ability to write high-quality, reproducible research code. 
  • Mission Mindset: A strong desire to apply advanced research to solve tangible, real-world problems in a fast-paced environment. 

Benefits

We offer the following salary and benefits:

Enhanced holiday pay

Pension

Life Assurance

Income Protection

Private Medical Insurance

Hospital Cash Plan

Therapy Services

Perk Box

Electric Car Scheme

--

Why work for EIT:

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!

Skills Required

  • PhD in Machine Learning, AI, Computer Science, Physics, Mathematics, Computational Biology, or a related quantitative field, or equivalent experience
  • Proven track record of impactful research, such as publications in top-tier AI venues or scientific journals
  • Deep expertise in deep learning frameworks
  • Ability to write high-quality, reproducible research code
  • Experience building simulation-based pipelines to predict experimental outcomes and using machine learning to accelerate those pipelines
  • Experience with production-grade pipelines for small molecules, biomolecular design, and simulations
  • Ability to build and validate end-to-end machine learning pipelines and in-silico design-build-test loops
  • Strong desire to apply advanced research to tangible real-world problems in a fast-paced environment
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The Company
HQ: Oxford
Year Founded: 2023

What We Do

The Ellison Institute of Technology aims to discover, develop, and deploy science and technology to solve humanity's most important problems, focusing on health and medical science, food security, climate change, and AI-driven government innovation.

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