Job Description

REQ ID: 116991
JOB TITLE: Efficiency Model Based Controls Engineer 25 July 23
SALARY: \xc2\xa336,700 - \xc2\xa348,600
POSTING END DATE:
LOCATION: Warwickshire

We\'re re-examining our vehicles and what a vehicle means in the emerging world of automation, connectedness, electrification and the shared economy. New ideas, new technology, and new approaches to mobility are our business. Join a team of next generation thinkers.

WHAT TO EXPECT

A talented Engineer is sought in support of creating artefacts for vehicle efficiency control functions which are model based. This is an opportunity to use physics based high fidelity models and create functional blocks of model based controller and energy optimisers primarily.

This is an exciting space to be part of as you have access to data lakes and get to use surrogate modelling, data modelling, artificial neural network & model order reduction for creating the functional blocks to be implemented into control system for thermal & electrical efficiency of JLR vehicles. You get to combine domain knowledge of thermal and electric energy management with data and artificial intelligence based advanced controls.

Key Accountabilities and Responsibilities

• Interrogate physics-based energy & thermos-fluid models and create functional model blocks for controller implementation by control systems team.
• Creating reduced order models for real time controller implementation.
• Create surrogate models from 3D & 1D CFD models output, chose right training data set and data training protocol; They can range from polynomial response surfaces to Bayesian networks or Gradient enhanced kriging (GEK) or Artificial Neural Network (ANN).
• Create virtual sensors where necessary for solving thermal & electrical energy management control optimisation problems.
• You get to collaborate with the Control System Domain teams for implementation of the function blocks.
• Support the automation of data pipelines feed into the optimisers and models for thermal and electrical energy management.

WHAT YOU\'LL NEED

We are keen to secure someone with experience or theoretical knowledge of the following (perhaps as a Masters, PhD graduate or Research Associate) that has a background in Physics, Mathematics, Statistics or Computer Science along with exposure to thermal, electrical and energy management principles & theories.

You will have expeirence or knowledge of the folloiwng too:

• Bayesian modelling and/or Machine Learning background.
• Experience with surrogate modelling.
• Proficient in Matlab, Matlab Simulink, Matlab Deep Learning toolbox & Python
• Experience with Machine Learning Libraries e.g., PyTorch/Keras/Tensorflow
• Model Order Reduction - concept level understanding

SO WHY US?

Bring all this to the home of premium innovation, and you\'ll find the opportunities to further your career with a world-class team, a discounted car purchase and lease scheme for you and your family, membership of a competitive pension plan and performance related bonus scheme. All this and more makes Jaguar Land Rover the perfect place to continue your journey.

This role may offer the opportunity for hybrid working where you can split your time between working from home and in the office. At Jaguar Land Rover, hybrid working is a voluntary, non-contractual arrangement providing employees with more choice and flexibility around how, when and where they work, if suitable for their role. Further details can be discussed with the Hiring Manager at interview stage.

Please be aware that we may close this vacancy for applications before the stated deadline if we receive a high volume of interest. We strongly advise you to submit your application as early as possible.

Jaguar Land Rover is committed to equal opportunity for all.

Jaguar Land Rover