Simulation / Bayesian Data Scientist

Job Description

Simulation / Bayesian Data Scientist(London onsite)

Who are CloudNC?

At CloudNC we are ambitiously and successfully developing deep technology that automates CNC Manufacturing. We have a factory running commercially to produce intricate and high-specification work for our clients which allows us to also tie in our software to a tangible, physical output.

In excess of £150 Bn worth of components are produced using CNC machines every year. The industry is reliant heavily on human input, it is slow and costly. Demand and value of the industry is rapidly growing, as are the increased demands on a vanishing workforce (50% will retire within the next decade).

We are driving a manufacturing revolution (Industry 4.0) and we have achieved notable success and world firsts where others have failed. We are ambitiously scaling up with credible backing, with incredible backers, and exceptional teams. We have been featured in Forbes and technology linked organisations (e.g. TechCrunch, The Engineer etc.), we were awarded and named as Technology Pioneers by the World Economic Forum and our founders are listed in the Forbes 30 under 30.

What it’s like to work together.

With our recent successful investment round, we are now embarking on a strong scaling plan over the short/medium and long term - pivotal to this success are the people.

Our teams have their own individuality and operate with their own cadence, we would love to have those discussions with you during the interview process. We are guided by the mission and by being humans of empathy, intellectual curiosity, collaboration, and continuous improvement/development (of self and the team).

We are over 80 people strong, with the ambition to double this headcount in the near future. We encourage your thoughts and feedback to help shape the company, whether through direct correspondence, Peakon platform, open door time and other channels.

We operate a “flexible first” environment, our HQ office is based in London and our modern factory is based in Chelmsford, Essex.

The Role

To combine physics, engineering and data science principles with rigorous problem solving to develop models to underpin our autonomous manufacturing technologies, serving both internal and external customers.

To work as part of the Factory R&D team, collaborating with software engineers, production engineers, machinists and product owners:

*To develop parameterisable, physically-based models of phenomena where the underlying physics is suffciently well understood.

*To develop data driven, parameterisable models (for example Bayesian inference or machine learning) where physical models are not suitable.

*To gain, through design of suitable experiments, and analysis of rig and machine data, fundamental understanding of the machining process.

*To apply multi-objective optimisation techniques to maximise efficiency, quality, and repeatability of end-to-end production processes.

*To apply suitable methods to understand correlation/causality between observed phenomena, and for the rapid identification of abnormal behaviour.

Principal accountabilities

Develop and correlate robust simulation models of aspects of the production process (currently focussing on milling) through experimentation, analytics, and use of existing research:

*Propose, implement and test new models - or refinements to existing models - associated with key metrics such as tool wear, finished surface geometric accuracy, surface quality, and vibration.

*Work with other stakeholders to identify key areas of the model for improvement.

*Conduct research to support applicable model development and analytics techniques.

*Assist with hands-on development, commissioning and running of rigs required to gather data to support model development.

*Contribute to planning and reporting activities in order to support business and specification development, including delivering presentations to key stakeholders. Share knowledge and understanding of new techniques used.

Skills and Experience sought.

*Outstanding academic background with MEng or PhD in Mechanical Engineering/Mathematics/Physics or related discipline

*Experience of application of Bayesian inference, and other machine learning techniques.

*Ability to quickly understand complex problems and implement a route to solve them.

*Ability to clearly and concisely communicate technical information.

*Experience using and developing models in Python and/or C++, Maple, Julia, Matlab.

*Ability to manage time on concurrent projects while working with different stakeholders.

Equal opportunities statement.

We are proud to be an equal opportunity employer, valuing individuality and embracing all people. The success of CloudNC is a result of diversity of thought. We recognise this comes from people truly belonging. We encourage different perspectives and skills to collaborate towards our mission – disrupting the manufacturing industry. We celebrate diversity and continually improve our inclusivity efforts.