Machine Learning Engineer
Bind Research is an innovative not-for-profit research organisation at the forefront of developing tools and datasets to characterise small-molecule interactions with intrinsically disordered proteins. Based just a short walk from Kings Cross station, Bind leverages interdisciplinary methods that span experimental biophysics – with a strong focus on nuclear magnetic resonance (NMR) spectroscopy – as well as computational approaches and cellular studies. You will play a crucial role in shaping the future of this cutting-edge research initiative.Join Bind Research and help push the limits of drug discovery for intrinsically disordered proteins. If you are dedicated to supporting the advancement science and technology in an innovative environment, we encourage you to apply!Role OverviewWe are seeking a Machine Learning Engineer to advance data-processing and model-building and deployment capabilities at Bind. This role includes developing new machine-learning models for highly complex and heterogeneous scientific data such as from nuclear magnetic resonance (NMR), deploying and productionizing these models internally and externally, contributing to open-source software, and large-scale data analysis, curation, and pipeline building.Key ResponsibilitiesDevelop innovative machine learning approaches to elucidate and quantify the interactions between small molecules and intrinsically disordered proteinsIntegrate molecular simulations and deep learning approaches using cutting-edge architecturesSoftware EngineeringEnhance the usability of built models by implementing automated, streamlined, and efficient software solutions in line with best practicesUtilise active learning, Bayesian, and bootstrapping methods to achieve robust performance in low-data regimes, and make use of distributed training methodologies for large modelsBuild model-deployment and job-launching systems for internal and external useCollaborate closely with other computational and NMR team members, in addition to experimental biophysicists, assisting with experimental data handling and curationAssist in optimising data collection practices in both computational and experimental teamsMentor and support Bind’s interdisciplinary team in machine-learning and data analysis methodsDriving InnovationStay current with breakthroughs in machine learning, neural networks, NMR, and computational technologiesContribute to the design and execution of cutting-edge machine learning and NMR research projects that advance Bind’s scientific missionThrive in a dynamic, start-up-style environment where initiative and flexibility in your role are valued.Qualifications and ExpertiseWe encourage applications from software engineers, scientists, and individuals with relevant transferable skills who are enthusiastic about our mission to make disordered proteins druggable, even if they do not meet every requirement listed below. We believe innovation thrives through diverse perspectives and welcome candidates from both academic and industry backgrounds.Education and ExperienceMSc in a technical field with 3 years of machine learning or model-building experience or a PhD with a similar focusExtensive knowledge of machine learning approaches, neural network architectures, training methods, and data preparation best practicesExperience in applying machine learning and modelling techniques to graph-based data such as molecules and proteins, as well as time seriesStrong dev-ops skillset, with proficiency in model deployment, versioning, distributed architectures, and containerizationTrack record of completed scientific software projects or open-source project contributionsSkills and AbilitiesStrong written and verbal communication skills, with the ability to communicate effectively with team members in diverse fieldsStrong programming abilities in Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQLExpertise with deep learning approaches such as diffusion or flow matchingProficiency in modern software development practices: code testing, documentation, packaging and deployment, version control using Git, containerizationProven ability to process, analyse, and present large and complex datasets using techniques such as clustering and dimensionality reductionAdditional AttributesA collaborative mindset and an enthusiasm for interdisciplinary teamworkA strong engineering mindset: you believe ease-of-use, reproducibility, maintainability, and clear documentation are key requirements for scientific software and allow complex projects to gain results fasterDedication to continuous professional development in machine learning, dev-ops, programming, and a willingness to learn more about experimental biophysical methodsPassion for contributing to the establishment and growth of a world-class not-for-profit research organisationNice to HaveKnowledge of NMR spectroscopy and associated data processing pipelinesFamiliarity with simulation techniques such as molecular dynamics or Monte Carlo approaches, as well as an understanding of statistical mechanics and complex systemsAbility to use HPC and / or cloud computing and building automation and orchestration systems for these platformsProficiency in a low-level language such as C, C++, or Rust and in GPU frameworks like CUDACompetence in front-end web design to allow easy interfacing with large datasetsOur CultureFollow the science. We prioritise rigorous scientific inquiry, relying on evidence and expertise to guide decisions and actions, incorporating the latest research to achieve meaningful, ethical, and impactful outcomes for the public and scientific community.Think dynamically. We believe the most effective solutions come from a dynamic, adaptable mindset that embraces uncertainty as a catalyst for discovery, encouraging creativity, challenging assumptions, and approaching problems from multiple angles to foster innovation, navigate complexity, and deliver exceptional results.Celebrate a diverse ensemble. We celebrate diversity and inclusion, fostering a culture where all perspectives, backgrounds, and talents are valued, respected, and empowered to thrive, enabling us to better understand our community, collaborate effectively, and deliver impactful solutions.Build an innovation hub. We strive to advance disordered protein research by creating and sharing tools and datasets collaboratively, building on past contributions, and working alongside the disordered protein community to deepen understanding and maximise collective impact.What We Offer38 days holiday (inclusive of bank holidays)Employer pension contribution in line with market standardsCycle to work schemeLife insuranceAdditional informationThe interview process will begin with a phone screen. Successful candidates will then be invited to more comprehensive technical and cultural interviews.To apply send your CV and cover letter to careers@bindresearch.org with the reference number BRJ017 and your name in the email header.Join Bind Research and help push the limits of drug discovery for intrinsically disordered proteins!We are committed to protecting your personal information. For full details on how we collect, use, and store your data during the recruitment process, please refer to our Privacy Notice .
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