Senior Scientist/Principal Scientist AI/ML

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    "description": "<p><span style=\"font-weight: bold\"><span><span>About Maxion </span></span></span><span> </span></p>\n<p><span><span>Maxion Therapeutics is a biotechnology company developing antibody-based drugs for previously untreatable ion channel- and G protein-coupled receptor (GPCR)-driven diseases, including autoimmune conditions, chronic pain, and cardiovascular disease.</span></span><span> </span></p>\n<p><span><span>The Company is developing a pipeline of potentially first- and best-in-class therapeutics using its proprietary </span><span>KnotBody</span><span>®</span><span> technology to generate potent, selective, and long-acting therapeutics by combining naturally occurring mini-proteins (‘knottins’) with antibodies using </span><span>state-of-the-art</span><span> phage and mammalian display technologies.</span></span><span> </span></p>\n<p><span><span>Maxion was founded in 2020 by highly respected biotech entrepreneurs and scientists Dr</span><br><span>John McCafferty</span><span> (</span><span>CTO</span><span>)</span><span> and Dr Aneesh </span><span>Karatt-</span><span>Vellatt</span><span> (</span><span>CSO</span><span>)</span><span>. Dr McCafferty previously co-invented antibody phage display, which was the subject of the 2018 Nobel Prize in Chemistry awarded to his co-inventor Sir Gregory Winter. Maxion’s portfolio and growth is being advanced by a team of highly experienced leaders in the discovery and development of antibody-based drugs. The Company is based near Cambridge, UK and is backed by international blue-chip investors. For more information, please visit:</span></span><span> </span></p>\n<p><a href=\"https://www.maxiontherapeutics.com/\" target=\"_blank\" rel=\"noopener noreferrer\"><span><span>https://www.maxiontherapeutics.com/</span></span></a><span><span>.</span></span><span> </span></p>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>About the Role</span></span></span><span> </span></p>\n<p><span><span>We are<span> </span></span><span>seeking</span><span><span> </span>a highly skilled Senior AI Research Scientist with<span> </span></span><span>expertise</span><span><span> </span>in computational protein design and generative protein modelling to enabling AI- and structure-guided approaches to therapeutic antibody and<span> </span></span><span>KnotBody</span></span><span><span>®</span></span><span><span><span> </span>design.</span></span><span> </span></p>\n<p><span><span>The successful candidate will drive the development, implementation,<span> </span></span><span>deployment</span><span><span> </span>and adoption of generative AI/ML models to enable therapeutic protein design,<span> </span></span><span>engineering</span><span><span> </span>and optimisation, utilising Maxion’s proprietary<span> </span></span><span>KnotBody</span></span><span><span>®</span></span><span><span><span> </span>technology. </span></span><span> </span></p>\n<p><span><span>This is a unique opportunity for someone who is excited to roll up their sleeves, build new capabilities from the ground up, and drive forward discovery programmes. </span></span><span> </span></p>\n<p><span><span>The successful candidate will</span><span><span> </span>bring strong technical skills, a collaborative mindset, and the ability to thrive in a fast-paced biotech environment.</span></span><span> </span></p>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Key<span> </span></span><span>Responsibilities</span></span></span><span> </span></p>\n<ul>\n<li><span style=\"font-weight: bold\"><span><span>Develop the computational protein design platform</span></span></span><span><span> through integration, </span><span>adaptation</span><span> and benchmarking of generative protein design &amp; engineering tools (AlphaFold/</span><span>OpenFold</span><span>, </span><span>RFDiffusion</span><span>, </span><span>ProteinMPNN</span><span>, Boltz, </span><span>FrameFlow</span><span>, etc) into the drug discovery process.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span style=\"font-weight: bold\"><span><span>Build generative </span><span>and predictive models for </span><span>protein design</span></span></span><span><span> by training and fine-tuning ML models (VAEs, diffusion models, transformers) focused on prediction of functional therapeutic proteins and their properties (affinity, stability, and developability).</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span style=\"font-weight: bold\"><span><span>Enable computational optimisation</span></span></span><span><span> of therapeutic proteins, </span><span>leveraging</span><span> various</span><span> ML </span><span>approaches</span><span> </span><span>(genetic algorithms, Bayesian optimisation, physics-based methods, etc.) </span><span>and integrating experimental data.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span style=\"font-weight: bold\"><span><span>Build datasets</span></span></span><span><span>, data pipelines, training workflows, and evaluation tools for model training, benchmarking, and continuous learning.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span style=\"font-weight: bold\"><span><span>Cross functional collaboration</span></span></span><span><span> with internal R&amp;D and discovery teams to translate predictive models into deployable tools and testable experimental hypotheses.</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Candidate Profile</span></span></span><span> </span></p>\n<ul>\n<li><span><span>Ph.D. or MSc. in Computational Biology, Computer Science, Bioinformatics, Natural </span><span>Sciences</span><span> or a related subject.</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Essential skills/experience</span></span></span><span> </span></p>\n<ul>\n<li><span><span>Strong programming skills in Python and experience with deep learning frameworks (e.g. </span><span>PyTorch</span><span>, JAX, TensorFlow</span><span> in order of preference</span><span>).</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Substantial experience of structural bioinformatics and computational protein design, for example: protein structure modelling &amp; prediction, generative protein sequence &amp; structure design, protein-protein docking, physics-based modelling &amp; simulation, etc</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience training and fine-tuning ML models for protein design or related tasks.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience of integrating computational predictions with experimental validation data for property optimisation.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience working with modern </span><span>MLOps</span><span> stacks (Docker, Kubernetes, CI/CD, GitHub</span><span>, etc.</span><span>) to deploy and </span><span>monitor</span><span> models.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience working with antibody sequence and structure datasets, using </span></span><span><span>in silico</span></span><span><span> tools for predicting protein properties and guiding engineering campaigns.</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>Desirable</span><span><span> </span>skills/experience</span></span></span><span> </span></p>\n<ul>\n<li><span><span>Publication(s) in relevant peer-reviewed journals, ideally focused on antibody design, AI/ML based protein modelling, or non-standard scaffolds (e.g. knottins, </span><span>minibinders</span><span>, etc.).</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Experience applying generative or structure-based models to challenging target classes (e.g. ion channels, GPCRs).</span></span><span> </span></li>\n</ul>\n<p><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>What can we offer you?</span></span></span><span> </span></p>\n<ul>\n<li><span><span>A competitive salary based on experience</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>A comprehensive benefits package including generous pension contribution, Private Life and Medical Insurance, Cycle to Work Scheme, participation in the company Share Option Scheme, </span><span>on site</span><span> parking and more.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Significant opportunities for career progression within a dynamic company. </span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Located in a state-of-the art Science Park with easy access to Cambridge by car, train and bus, and offering on-site gym, cafe, and a vibrant social community.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>Working alongside an innovative team of scientists, including the founders, who are Key Opinion Leaders in the field.</span></span><span> </span></li>\n</ul>\n<ul>\n<li><span><span>A supportive work environment with a key focus on fostering collaborative working environment within a friendly team.</span></span><span> </span></li>\n</ul>\n<p><span><span>To apply for this position, just click on the link to upload your CV and covering letter outlining your suitability for this role, including your salary expectations.  Due to data safety, please do not email or apply via direct messaging.</span></span><span> </span></p>\n<p><span><br></span><span> </span></p>\n<p><span style=\"font-weight: bold\"><span><span>This is a permanent position.</span></span></span><span> </span></p>\n<p><span><br></span><br></p>\n<p><span><span>Agencies</span></span><span><span>: We are recruiting this role with our selected recruitment partner - <span>PIR International. If you need to get in touch regarding the role please reach out directly to the contact at PIR: <a href=\"mailto:[email protected]\" target=\"_blank\" rel=\"noopener noreferrer\">[email protected]</a> .</span></span></span></p>",
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