Research Scientist, Generative AI (Multimodal Foundation Models)

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.