Algorithm Engineer

<p><strong>ROLE: Senior Battery Algorithm Engineer (Senior to Principal Considered)</strong></p><p><strong>LOCATION: Oxfordshire</strong></p><p><strong>COMPENSATION: Market Leading</strong></p><p><br><br>Is this the role you are looking for If so read on for more details, and make sure to apply today.<br></p><p>TECHNE is supporting an advanced Battery Intelligence technology company in the search for a Senior Battery Algorithm Engineer to join their growing engineering team in Oxfordshire.</p><p><br></p><p>This role sits at the forefront of next-generation Battery Management Systems, focused on developing advanced embedded algorithms that directly impact battery safety, fast charging performance, degradation detection, lifetime optimisation, and real-world reliability.</p><p><br></p><p>You will work on highly complex nonlinear systems across temperature, ageing, and operational variability, translating advanced theory into embedded, production-ready solutions.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li>Develop advanced battery state estimation and control algorithms across multiple chemistries and operating conditions</li><li>Design diagnostics and prognostics algorithms for next-generation BMS platforms</li><li>Build robust observer architectures using EKF, UKF, Kalman Filters, MPC, and probabilistic estimation techniques</li><li>Deploy real-time embedded algorithm solutions</li><li>Lead simulation-based validation activities using representative drive cycles and ageing scenarios</li><li>Analyse cell, module, and pack-level datasets to identify performance limitations and edge cases</li><li>Support algorithm validation through cell testing and data interpretation</li><li>Collaborate with modelling, validation, embedded software, and systems engineering teams</li><li>Produce technical documentation covering validation, assumptions, and performance metrics</li></ul><p><br></p><p><strong>Required Experience:</strong></p><ul><li>Degree in Mathematics, Physics, Electrical Engineering, Mechanical Engineering, Statistics, Computer Science, or related STEM discipline</li><li>Experience developing estimation or control algorithms using EKF/UKF, Kalman Filters, MPC, or similar approaches</li><li>Strong understanding of nonlinear systems and estimation theory</li><li>Strong analytical and problem-solving capabilities</li><li>Experience working within multidisciplinary engineering environments</li></ul><p><br></p><p><strong>Desirable Experience:</strong> xwzovoh </p><ul><li>Battery algorithms including SOC, SOH, and SOP estimation</li><li>Physics-based battery modelling including DFN or SPM</li><li>MATLAB/Simulink and model-based development</li><li>PyBaMM, COMSOL, or similar battery modelling platforms</li><li>Embedded systems and embedded software deployment</li><li>Data-driven modelling, Gaussian Processes, or embedded ML</li><li>Battery testing and validation</li><li>ASPICE and CI/CD environments such as GitHub, GitLab, or Azure DevOps</li></ul><p><br></p><p>This is an opportunity to join a high-performing engineering environment developing advanced battery intelligence technology with direct impact on future mobility and energy systems.</p><p><br></p><p>If you would like to discuss the position confidentially, please get in touch directly</p>