Senior Battery Modelling Expert

4 months ago

London, United Kingdom Zenobē Full time

**ABOUT ZENOBE**

Our goal is to make clean power accessible, to accelerate the shift to zero carbon power and transport.

We’re building and operating the world’s most sophisticated battery systems to enable the uptake of more renewable power and accelerating fleet electrification, de-risking the transition to zero-emission transport at scale. We’ve been consistently innovative since we were founded in 2017, achieving major industry firsts and using proprietary software and data analysis to optimise operational performance for our customers. At the end of their life, we repurpose electric vehicle batteries to provide clean power at depots, on construction sites and film sets.

Today we have 730 MW of grid scale battery storage operational and under construction and are the largest owner and operator of EV buses in the UK, Australia and New Zealand, supporting over 1,000 electric vehicles worldwide. In our first five years we have raised nearly £1.8 billion in funding and have expanded into other markets such as the US. Our rapidly growing company is looking for highly talented and motivated people to join us.

**THE OPPORTUNITY**

We are looking for a Senior Battery Modelling Expert, Engineer or Data Scientist with a background in lithium-ion battery modelling for performance and degradation. As part of the EV Fleet Analytics team, within the Commercial Analytics department, you will work closely with our software, data science, data engineering and operational teams to successfully model the short and long-term performance of batteries, allowing the optimisation of EV fleet operations. Typical duties include developing calculation logic for accurate SoC and SoH determination, building digital-twin models of EV batteries and forecasting degradation over EV fleet lifetimes. The wider EV Fleet Analytics team are responsible for optimising all aspects of EV operations and performance (i.e. efficiency, charging strategy, commercial performance), of which battery performance is a key aspect. Battery models are used across the business to underpin our offering and as such this role will engage on a wide variety of projects and teams from engineering to financial.

**A TASTE OF THE DAY TO DAY**
- Work with large fleet datasets to train machine-learning models for predicting battery degradation with support from the Data Science team.
- Physics-based modelling to inform battery performance in varying environments and guide charging performance on a vehicle and fleet level. (e.g. electric-equivalent, electro-thermal, digital twin, P2D)
- Researching, benchmarking and developing battery data processing logic for downstream analysis, modelling and reporting activities (e.g. SoC, SoH)
- Managing relationship and assessing third party battery insight providers (SOH, degradation)
- Work with the business development and operational teams to provide in depth modelling insights on fleet sites for both design-phase and live operational projects.
- Work with the software team to deploy simulation and analytics capabilities into automated pipelines linked with live data feedback and providing fleet performance insight or adapting future fleet strategies for continual improvement.
- Take a lead in shaping data pipelines from fleet telematics acquisition to processing and model training, especially in the battery performance and health data area.
- Engage with testing and operations team to devise instrumentation requirements and testing plans in support of model development and correlation (e.g. charging, battery degradation or vehicle energy consumption models).
- Continuously develop our analysis processes to increase efficiency and add value to all areas of the business.

**WHAT WE’RE LOOKING FOR**

**Essential skills, qualifications and experience**:

- STEM qualification (e.g. engineering, applied physics, (electro)chemistry, data science), 1st or 2-1
- PhD or Masters level degree related to battery chemistry / physics
- Technical background with good understanding of the underlying physical principles related to electric vehicles and the energy sector.
- A strong understanding of battery chemistry and performance aspects (e.g. degradation).
- 2+ years of relevant professional experience working at the cutting edge of the EV or renewable energy sector, focussing on modelling, simulation, analysis and data science for battery performance and degradation.
- Physics / Chemistry-based Python modelling experience (electric-equivalent, electro-thermal, digital twin, P2D)
- Machine learning modelling experience (battery ageing / degradation)
- Data science / data processing experience related to battery performance data (SoC / SoH calculation logic)
- Battery testing procedure specification for characterisation (cell & pack)
- Strong Python experience (numpy, scipy, pandas, matplotlib, plotly, poetry, GIT, scikit-learn and other scientific libraries)
- Excellent mathematical, analytical and problem-solving ability
- Ex

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