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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Computational Chemist - **Company:** Itec Select - **Location:** Manchester, UK (Remote available) - **Experience:** Expert - **Salary:** £60,000 - **Contract:** Temporary to permanent - **Skills:** Code Review, Computer Simulation, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Machine Learning, Microsoft Dynamics, Molecular Modeling, High Performance Computing, Performance Monitor, Slurm, Machine Learning Operations, Docker - **Published:** November 9, 2026 - **Apply:** https://www.jobs.service.gov.uk/jobs/6af1e4b0d90dd1b95e8fda8a/apply ## About the Role Proven hands-on experience developing or adapting machine-learning models and force fields for molecular systems. - Strong computational chemistry and molecular simulation experience, including quantum chemistry and molecular dynamics. - Experience modelling metal-containing and biomolecular systems. - Extensive, practical experience using HPC and GPU computing environments. - Strong Python programming skills and experience automating scientific workflows. - Experience using HPC schedulers such as Slurm or an equivalent platform. - Experience building reproducible training or simulation pipelines. - Strong understanding of metal coordination chemistry, including coordination motifs, oxidation states and binding geometries. - Ability to troubleshoot complex problems independently across simulations, model training, datasets and computing infrastructure. - Strong communication skills, particularly when explaining computational evidence, limitations and recommendations to experimental scientists and other stakeholders. - The independence and adaptability needed to succeed in a fast-moving, early-stage environment. - Early-stage biotechnology or startup experience. Relevant technologies Experience with some of the following would be particularly useful: CP2K ORCA VASP Quantum ESPRESSO NWChem Slurm or equivalent workload schedulers Docker Singularity or Apptainer Weights & Biases MLflow Scientific Python and molecular simulation software Qualifications and experience You should have one of the following: A relevant PhD plus at least three years of relevant industry or professional research experience; or A relevant MSc plus at least five years of relevant professional experience. Desirable experience - Protein or peptide design. - Metal-protein or metalloprotein systems. - Thermodynamic calculations and quantitative assessment of molecular interactions. - Model uncertainty estimation and data-quality assessment. - Experiment tracking and performance optimisation. - Mentoring or technical leadership. - Collaboration with wet-lab scientists. - Intellectual property generation or research commercialisation. What success will look like During the first three to six months, the successful candidate will be expected to deliver: - Validated molecular machine-learning models benchmarked against appropriate computational and experimental references. - Reliable predictions that directly inform experimental decisions. - Clearly documented model accuracy, uncertainty, assumptions and limitations. - Reproducible computational workflows with appropriate quality controls. - A clear technical roadmap covering milestones, risks and computing requirements. - Effective knowledge transfer between computational and experimental teams. ## Description The company is developing innovative biotechnologies for the selective binding and recovery of metals from waste streams, including electronic waste. This is a hands-on senior position offering ownership of technical strategy, scientific quality and delivery. You will work closely with computational scientists, wet-lab researchers, founders and external stakeholders to guide experimental priorities, solve complex modelling challenges and identify opportunities for intellectual property generation. Key responsibilities - Own and develop the machine-learning and molecular-modelling roadmap, including priorities, milestones, validation standards and computing requirements. - Develop, adapt and validate machine-learning models and force fields for molecular applications. - Lead the generation and quality assurance of computational datasets. - Run and interpret quantum chemistry calculations and molecular dynamics simulations. - Model metal-containing, biomolecular and coordination-chemistry-rich systems. - Benchmark computational models against appropriate theoretical and experimental references. - Diagnose and resolve issues involving electronic structure calculations, SCF convergence, molecular dynamics, model training, data quality and HPC environments. - Build and maintain reliable, scalable HPC and GPU workflows across cloud and research computing infrastructure. - Automate scientific workflows, training pipelines, experiment tracking and performance monitoring. - Translate modelling results, uncertainty and limitations into clear recommendations for experimental colleagues. - Contribute to technical strategy, programme planning and potential intellectual property generation. - Provide technical leadership through method selection, code review, mentoring and scientific problem-solving.