Job Description

Role Summary

DeepForm Ltd is an early-stage start-up company introducing patented sheet metal pressing technology that significantly reduces waste, cost, and embodied CO? emissions in the high-volume manufacturing of sheet metal components. DeepForm optimises material use by reimagining metal sheet forming tooling.

We are an exciting University of Cambridge spin-out company founded in 2022. Having secured external investment and formed a strategic alliance with a well-known automotive manufacturer, we are now securing our first major projects. This is an exciting time to join at the very early stages of the company's mission to reduce waste and embodied emissions in the manufacturing sector.

This will include recognising and extracting key features of component geometries; parameterisation of forming simulation; using suitable optimisation techniques to improve the quality of solutions; and developing an overall system to automate workflow.

From time to time, you may also be required to contribute directly to specific projects in which we use DeepForm's patented design methodology to design sheet pressing process layouts to maximise material utilisation, with a likely focus on components used in vehicle bodies.

Key Responsibilities

Recognising and extracting key features of target products:

Identify geometrical features following surface segmentation and other critical process parameters based on our knowledge base and customer needs.

Parameterisation of process simulation inputs and quality metrics:

Generate parameterised FEA models and measure simulation output performance.

Use and evaluation of appropriate techniques to generate optimal process designs:

Identify and compare appropriate data-based optimisation approaches. Combine FEA results and expert input as input to optimise tool designs.

Developing a system to automate full workflow:

Link existing and new digital processes to minimise human intervention. Identify areas for possible streamlining and re-structuring approaches to improve performance.

Person Profile

This section details the knowledge, skills, and experience we require for the role.

Background and experience:

You will likely have a degree in Engineering, Computer Science, Physics, or Mathematics. Experience in Machine Learning or Optimisation is also required.

Flexible and motivated to support rapid growth of a new business (Essential):

Independent self-starter, able to consult when key choices need to be made. Flexible approach to working in an exciting small team with developing formal structures.

Experience of developing software to solve optimisation problems (Essential):

Past experience with data-based engineering optimisation approaches. Relevant methods include the application of Bayesian optimisation and dimensional reduction. Employ mathematical optimisation towards manufacturing production design.

Experience of a systems engineering, machine learning, or operations research approach to workflow improvement (Essential):

Ability to develop a software platform to link, automate, and optimise existing and new digital workflows.

Excellent teamwork and project management (Essential):

Ability to manage time, communications, and project objectives to ensure projects are delivered on time and within budget.

Ability to operate in a team environment, collaborate with others, and interact with external partners. Knowledge of geometrical manipulation and FEA packages (Desirable):

Understanding of discrete geometry representation and common geometry characterisation techniques. Prior experience with solid mechanics and FEA simulation approaches.

Working pattern

Full-time, office-based, with some flexibility for hybrid working.

Benefits

Competitive salary Share option scheme Pension scheme 25 days' annual leave excluding bank holidays

Location

Allia Future Business Centre, Kings Hedges Road, Cambridge, CB4 2HY, United Kingdom

Interviews

In person interviews will take place in Cambridge on the week commencing 23 June.

Job Type: Full-time

Pay: 30,000.00-60,000.00 per year

Benefits:

Company pension
Schedule:

Monday to Friday
Experience:

Machine Learning: 2 years (preferred) geometry processing: 2 years (preferred)
Work Location: Hybrid remote in England, CB4 2HY

Application deadline: 29/05/2025
Reference ID: Optimisation Specialist