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Machine learning & Battery Modelling Engineer, London



Addionics Company


Addionics is a rapidly growing company focusing on the creation and development of the next generation of battery technology through innovative breakthrough methods. Addionics overcome challenges in existing battery technology to result in significantly improved batteries with greater capacity, faster charging and other performance characteristics. Addionics' unique technology enables battery development tailored for consumer electronics, micro-mobility, EVs and other applications. Addionics currently operates in two countries and works with different partners around the world.


General job description


Addionics is looking to employ a Machine learning (ML) & Battery Modelling Engineer who will be responsible for creating artificial intelligence (AI) solutions on electrochemical and thermo-mechanical models of the next generation of innovative lithium-ion batteries. It will involve working on patent-pending methods and new solutions for batteries at electrode, cell and system level. The candidate must have a legal right to work in the UK.


The focus will be development and implementation of ML algorithms and simulations of high-fidelity models of Addionics battery designs and electrode technology. The candidate will be response to facilitate battery design from a fundamental level to enhance optimization of performance using ML techniques; working alongside other team members and Addionics solutions. The successful candidate will therefore help develop ground-breaking solutions to resolve pore-scale transport processes and understand structure-performance relationships that will serve as a benchmark and guide for future designs and operation of emerging lithium-ion battery technology. The role will involve highly innovative and close collaborations with senior battery scientists, industrial partners and Addionics’ team in Israel. The candidate should be a strong self-motivator, with capable skillset in batteries and machine learning. The candidate will report to the company’s directors from time-to-time and work within the offices based in Central London. The candidate will take pride in the unique new role and maintain our high quality of work.


A holder of the position will play a vital role in planning and successfully running and completing important AI informed designs of electrode microstructures which will help determine R&D directions and scaling -up.




  • Develop machine learning and AI applications enhancing Addionics’ battery designs;

  • Help develop multiscale physics based models of lithium-ion batteries;

  • Translate the results of physics based models into system level performance;

  • Work with experimentalists to gather data for the parameterization and validation of models;

  • Perform analytical work on optimized parameters and model outputs;

  • Work very closely with company team members and other project partners;

  • Attend progress and project meetings;

  • Write progress reports;

  • Promote the company at external events; 

  • Transfer simulation analysis into real world products; 

  • Build a portfolio of ML based models to meet the company targets;

  • Develop strong and healthy collaboration with the team in the UK and with the other R&D teams and functional groups in Israel;

  • Participate in planning process optimization and production scaling up;



  • PhD related to Mathematics, Statistics and ML algorithms. Preferably with understanding of electrochemical, mechanical and thermal modelling. Backgrounds such as Mechanical/Materials/Chemical Engineering or a closely related discipline, or equivalent research, industrial or commercial experience are suitable

  • Experience in managing and developing machine learning/AI projects

  • Experience with electrochemical devices

  • Experience with modelling techniques

  • Professional experience with Python using standard libraries and Matlab/Simulink and other programming languages such as C/C++, Python or Java

  • Professional experience in TensorFlow, PyTorch and equivalent

  • Problem-solving capabilities

  • Team player with excellent communication skills




  • Experience with Multi-physics modelling software such as COMSOL

  • Understanding system level simulations

  • Experience with testing batteries or working with experimentalists

  • Experience in working in a software development environment

  • Experience in the area of image-based simulations

  • Experience in using machine learning for data analysis 

  • Experience in creating GUI

  • Experience in working in a multidisciplinary research environment and across multiple institutions

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