InstaDeep, founded in 2014, is a pioneering AI company at the forefront of innovation. With strategic offices in major cities worldwide, including London, Paris, Berlin, Tunis, Kigali, Cape Town, Boston, and San Francisco, InstaDeep collaborates with giants like Google DeepMind and prestigious educational institutions like MIT, Stanford, Oxford, UCL, and Imperial College London. We are a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner. We have been listed among notable players in AI, fast-growing companies, and Europe's 1000 fastest-growing companies in 2022 by Statista and the Financial Times. Our recent acquisition by BioNTech has further solidified our commitment to leading the industry.
We are seeking Research Scientists to join our London-based Research Team, working at the forefront of generative AI and its applications in life sciences. Our team is dedicated to building foundational expertise and developing the next generation of deep learning technologies. Roles are available for both recent graduates and senior profiles.
Generative foundation models like ESM-3 [1], AlphaFold [2], RFDiffusion [3], ProteinMPNN [4] are revolutionising computational biology and in silico drug design; and InstaDeep is leading the way in developing the next generation of technologies and applications (see as examples, Nucleotide Transformer [6] and ProtBFN [7]). This requires pushing the boundaries of both fundamental aspects of generative AI - including new algorithms, enhanced sampling and reasoning techniques - and the development and validation of these ideas for biological domains. As a Research Scientist at InstaDeep, you will have the opportunity to:
Advance Foundational Research Tackle challenges in generative modelling, such as handling heterogeneous, multimodal, and noisy data, and developing effective sampling algorithms for both conditional and unconditional generation.
Develop Biological Foundation Models Contribute to the creation of new models that push the boundaries of what's possible in computational biology.
Collaborate Across Disciplines Work closely with Machine Learning Engineers, Research Engineers, Computational Biologists, and other experts.
Leverage Cutting-Edge Resources Utilise our near-exascale supercomputing cluster, `Kyber` [9], to conduct large-scale training and evaluation of generative models.
Publish and Present Research Share your findings at top-tier conferences and in leading journals.
Responsibilities
- Innovate in Deep Learning Research Develop and implement novel research on multimodal generative foundation models and their biological applications.
- Contribute to Team Success Collaborate with team members to achieve research goals and contribute to a supportive, knowledge-sharing environment.
- Engage in Collaborative Projects Initiate and participate in collaborations with external partners and internal departments, including our applied BioAI team and strategic partners like BioNTech.
- Communicate Findings Report and present experimental results and research insights both internally and externally, through presentations, written publications and representing InstaDeep at conferences and events.
Requirements
- Research Experience: Experience in professional research settings, either in industry or through PhD/post-doctoral positions.
- Proven Research Excellence: A strong track record of high-quality research, evidenced by publications in reputable scientific journals or conferences.
- Expertise in software development and programming in Python.
- Experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow.
- Excellent ability to communicate complex ideas clearly, both verbally and in writing, and to work effectively within a multidisciplinary team.
- Strong analytical and critical thinking skills with the ability to adapt to a dynamic research environment and tackle complex challenges creatively.
- Demonstrated enthusiasm for continuous learning, staying updated with advancements in AI, and contributing novel ideas to the field.
Desired Skills
- For senior roles who would be interested in leadership positions, experience mentoring junior team members, leading research projects, and guiding collaborative efforts is a plus.
Knowledge of the following machine learning domains is a plus.
- Generative models leveraging diffusion or Bayesian Flow Networks [8].
- Modelling multimodal data.
- Large-scale distributed machine learning training.
Knowledge, experience or interest in the following biological domains is a plus.
- Drug discovery and protein engineering.
- Understanding of protein language models and structural proteomics.
- Knowledge of genomics.
References
[1] Simulating 500 million years of evolution with a language model
[2] Accurate structure prediction of biomolecular interactions with AlphaFold 3
[3] De novo design of protein structure and function with RFdiffusion
[4] Robust deep learning–based protein sequence design using ProteinMPNN
[5] Bayesian Flow Networks
Selected InstaDeep publications and releases
[6] The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics
[7] Protein Sequence Modelling with Bayesian Flow Networks
[8] A foundational large language model for edible plant genomes
[9] Kyber is InstaDeep’s in-house cluster and ranks among the world’s top 100 most powerful clusters and is among the top 20 H100 GPU clusters.
Our commitment to our people
We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this than by joining our team? We operate on a hybrid work model with guidance to work at the office at least 2 to 3 days per week to encourage close collaboration and innovation. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.
Right to work Please note that you will require the legal right to work in the location you are applying for.
