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Research Engineer: ML for Life Sciences & Protein DesignInstaDeep • London, England, United Kingdom
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Research Engineer: ML for Life Sciences & Protein Design

InstaDeep
  • GB
    London, England, United Kingdom
  • GB
    London, England, United Kingdom
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À propos

InstaDeep is looking for Research Engineers to join our Research Team in London, working at the intersection of machine learning and life sciences. Our in-house Research Team aims to build foundational expertise and develops the next-generation in of deep learning technologies for life science applications; for example, generative models for protein sequence and structure, protein structure prediction and inverse folding, ML-enhanced molecular dynamics, learning meaningful representations from proteomics datasets, and more. This necessarily requires expertise not just in machine learning, but also in the curation of experimental data and computational modelling techniques such as homology modelling, molecular dynamics with classical force fields, quantum chemistry calculations with density functional theory. As a Research Engineer, you will work closely with our Research Scientists to support our ambitious research agenda. Responsibilities Collaborate within the Research Team and other in-house experts to develop machine-learning methods for problems in computational biology. Implement and test novel research ideas. Leverage classical and/or deep learning biology tools and large biological databases to perform protein design, sequence optimisation, molecular modelling, and other relevant tasks. Contribute to the design and implementation of models, tools and libraries to accelerate our research effort. Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments. Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing. Contribute to the team's publication efforts. Bridge the gap between the research and product teams by integrating new fundamental research into applied projects. Requirements S./PhD in Computational Biology, Machine Learning or a related scientific field. Experience using Deep Learning frameworks like PyTorch, Tensorflow and/or Jax. Ability to understand, replicate and adapt to industrial standards research works Software engineering experience (Object-Oriented Programming, Unit Testing, Profiling, CI, Docker) via previous work or contributions to open-source projects. Excellent communication skills and collaborative spirit. Desirables Individuals in this role are expected to be accomplished in computational biology and machine learning. Experience with any of the following biological topics would be a plus. Experience working with large biological datasets, databases (PDB, Uniprot, etc.) and their API technologies. Protein language models Drug discovery and protein engineering Molecular dynamics Structural biology Experience, with any of the following machine learning topics would be a plus. Large Language Models Generative models
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  • London, England, United Kingdom

Compétences linguistiques

  • English
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