Why this role is important for CPI’s
work
CPI has an exciting opportunity for an Applied Data Scientist (Research Engineer – Digital Technologies) to join its established and growing Automation and Digital team within the Formulation Technology Team at our state of the art: , based at NETPark in Sedgefield.
The ideal candidate will be a cross-disciplinary thinker, combining expertise in chemistry, physics, biology, or mathematics with strong data science skills. In this role, you will leverage modern computational, statistical, and cloud-based technologies to generate insights into complex materials, driving innovations across energy storage, sustainable materials, nanotherapeutics, and consumer goods. A strong foundation in materials at the molecular, atomic, or structural level is highly valued, along with a keen interest in the markets we serve — particularly energy storage, pharmaceuticals, and sustainable materials. Experience in applying machine learning, high-dimensional modeling, or data-driven simulation on cloud platforms to address real-world materials challenges will allow you to make an immediate impact.
Reporting to a Team Leader, you will leverage your existing skills in data science and be further developed in strategically relevant areas such as Machine Learning (ML), Artificial Intelligence (AI), predictive modeling, automation of data capture/processing, and ML-driven Design of Experiments (DOE) methods. Using these skills across a combination of low-code platforms, Python scripts, and cloud-based technologies for scalable computation and data management, you will contribute to the delivery of innovation projects with our clients and support technical leads in providing advice and solutions to both internal and external stakeholders. In addition, this role offers a unique opportunity to contribute to the development and operation of our 24/7 robotic formulation laboratory, integrating advanced automation with data-driven experimentation to serve our markets.
The Automation and Digital team’s mission is to deploy digital and physical technologies that improve efficiency and quality when innovating in the formulation sector, and enable the generation, curation and analysis of large data sets to produce insights. We combine our digital skills with industrially relevant knowledge, laboratory automation and high throughput experimentation, and state-of-the-art process characterisation, to provide a complete solution for companies seeking to accelerate innovation for new and existing product lines.
The team works with companies and organisations of all sizes from global multinationals to 2‑person start-ups, with project durations ranging anywhere from 1 month to 4 years.
You will be exposed to an immense variety of projects: in scale (anything from 1 month to multi-year projects); in area of application (batteries, sustainability, nanotherapeutics, FMCG, food and feed sectors) and technical scope of the techniques used.
You will be encouraged to explore new techniques (techniques both new to our organisation, and novel techniques emerging from academia). Training in new techniques — whether self-taught, peer training or through formal courses — is encouraged.
Some exciting projects the team have recently worked on are:
BatCAT: BatCAT is the project that realizes the manufacturability programme from the BATTERY + Roadmap, creating a digital twin for battery manufacturing that integrates data-driven and physics-based methods. It develops a cross-chemistry data space for two technologies, (1) Li-ion and Na-ion coin cells and (2) redox flow batteries.
HealingBAT: Horizon Europe EU project is developing advanced sensing, monitoring and self-healing mechanisms to self-repair batteries, leading to the EU batteries of the future..
Narrator (Nanopharma): The application of state-of-the-art digital techniques and automation to explore Lipid Nanoparticle (LNP) manufacture for supporting RNA vaccines and therapeutics. Our digital scientists are helping to chart our way intelligently through libraries of chemical data and make strides in the science of LNP manufacture.
Full_Map: This project will help to develop our capabilities in our a fully automated R&D facility for battery manufacture and analysis from the formulation through to the cell manufacturing served by collaborative mobile robots.
Other types of projects that we run include:
Working with global leaders to apply model predictive control to their formulations. Using clustering and correlation analysis to determine cause-effects or comparisons within datasets (e.g., developing models to predict soap stability, predicting best candidates for new ink materials) Supporting development of our automated platforms in service of our markets Using machine learning techniques to on data to produce actionable insights. Developing soft sensors based on PLS and neural net models to predict slurry particle size and viscosity Implementing Bayesian methods and/or state-of-the-art methods for optimising the Design of Experiments approach. Developing a federated learning system to produce global models that enhance production in manufacturing.
The Role
Key tasks in the role will include (but are not limited to the below), please download the job description for full details available on the CPI careers page:
Supporting the planning and scoping of technical work programmes within digital strategy (e.g. model predictive control, process modelling, data analytics, machine learning, and the application of digital technologies). Undertaking the technical delivery of programmes of work in digital strategy on existing data or data collected from own experiments and researches, and then analysing, interpreting and reporting the results. Keeping up to date with research and techniques relevant to the digital space (e.g. develop in statistical modelling techniques, the mathematical foundations of applied machine learning, skills in process modelling and control, skills in relevant coding languages) and to develop, implement and improve existing methods/technologies in the platform. Growing as an internal expert in data science using knowledge of principles and practices in the field to support non-data science colleagues. Developing and utilising own expertise to build data science capability within the technology team and acting as internal consultant to coach others at CPI.
The person we are seeking
The successful candidate will be educated to HNC / Foundation Degree / Degree level (or equivalent) in a Scientific, Engineering or Mathematical discipline, plus relevant industrial experience in the application of data science in the prerequisite fields (see job descriptions for further information) and;
Will be able to solve and contextualise scientific problems using data science. Will possess willingness to learn new methods of datra science and coding languages. Can demonstrate the ability to apply theoretical and practical scientific methods to contribute to business activities. Will have confidence to use own judgement and initiative within standard engineering / scientific practices, as well as an understanding of when to seek advice from colleagues. Will possess knowledge of / have an awareness of one or more of the following data science and digital skills application methods;The application of advanced statistical methods (e.g. PCA) and modelling to technical problem-solving.The mathematical foundations of applied machine learningThe application of machine learning, process modelling or implementation of model predictive control.The use of coding languages (python, R Matlab) to create digital solutions for efficient or novel problem solving.The demonstration of technical and theoretical knowledge in mathematics related to data science Can demonstrate a working knowledge of the principles and practices in data science techniques gained through academia / career to date . Will have a background in / knowledge relevant to the batteries, energy storage and/or materials spaces Can demonstrate evidence of building knowledge sharing and communicating with non-specialist colleagues and stakeholders.
Applications are particularly welcome from candidates who are educated to Masters/PhD level (or equivalent) with relevant industrial experience and;
• Have some experience in using data science on cloud architectures
• Have chartered status with a relevant professional institution
• Are a member of a relevant professional body
What does CPI offer you?
At CPI, we offer a wide range of benefits to our employees, this includes:
Up to 36 days holiday, including bank holidays – Plus a holiday purchasing scheme Generous pension scheme Life assurance and accident insurance schemes Flexible working Learning and Development Opportunities Free parking
