System Modelling Lead


Details:
  • Salary: £60,000 - 70,000 - Annum
  • Job Type: Permanent
  • Job Status: Full-Time
  • Salary Per: Annum
  • Location: Cambridge Cambridgeshire
  • Date: 1 week ago
Description:

Factory-scale system modelling and optimisation

This exciting start up is transforming the state-of-the-art in biomedical processing, unlocking the door to large-scale affordable personalised medical treatments. Their core technologies are well-tested and ready for scale-up, but they need people with experience architecting, designing, developing, and optimising their factory-scale robotic systems.

With deep knowledge in system modelling and optimisation you’ll work alongside internal multi-disciplinary teams as well as external partners and customers to identify and assess critical details for the accuracy of the models. You’ll also provide invaluable advice and analysis at every stage in the development of this ground-breaking solution, giving you the unique opportunity to influence the future of medicine.

Requirements:
• Track record of applying Discrete Event Simulation techniques to aid in the design of large-scale real-world systems in the manufacturing, automation, or logistics industries.
• Knowledge of optimisation techniques such as mixed-integer linear programming, response surface methodology (RSM), and disjunctive programming.
• Good software development skills primarily utilising Python.
• Any additional knowledge or experience with operations research or cost modelling would be beneficial.

Situated in modern well-equipped facilities to the south of Cambridge, this team is growing fast with highly skilled engineers and scientists all knitted together with a strong belief in the potential of their technologies. With extensive funding already secured, on offer is a top package including generous pension and healthcare schemes.

Unfortunately, this company are currently unable to sponsor candidates and so you will need full and permanent rights to work in the UK to be considered for this role.

Keywords: Discrete Event Simulation, DES, Emulate 3D, Simul8, Anylogic, Mixed-Integer Linear Programming, MILP, Non-Linear Optimisation, Generalised Disjunctive Programming, Monte Carlo Simulation, Response Surface Methodology, RSM, Markov Chain, Petri-Net Analysis, Operations Research, Cost Modelling, Life Science

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