Data Scientist, PhysicsX
2-5 days a week in office (Shoreditch, London)
Machine learning for physics & engineering simulations
Open for applications
Machine learning for physics & engineering simulations
21-100 employees
Open for applications
2-5 days a week in office (Shoreditch, London)
21-100 employees
Company mission
To reimagine simulation for science and engineering using AI.
Role
Who you are
- We are looking for a capable and enthusiastic data scientist to join our team
- Enthusiasm about using machine learning for science and engineering
- Ability to scope and effectively deliver projects
- Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
- Excellent collaboration and communication skills - with teams and customers alike
- Degree in computer science, machine learning, applied statistics, mathematics, physics, engineering or a related field
- 2+ years’ experience in a data-driven role, with exposure to:
- Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, TensorFlow, PyTorch, Airflow), potentially including deep-learning applications
- Software engineering concepts and best practices for collaborative programming (e.g., versioning, testing, deployment)
- Working in a cloud environment with one of the major cloud providers
- (Appreciated, but not a prerequisite) Simulations for FEA/CFD
What the job involves
- Work closely with our simulation engineers, machine learning engineers and customers to develop an understanding of the physics and engineering challenges we are solving
- Build innovative models to predict the behaviour of physical systems leveraging state-of-the-art machine learning and deep learning techniques
- Own the delivery of data science workstreams
- Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
- Discuss the results and implications of your work with your colleagues and our customers
- Contribute to our internal R&D and product work
Salary benchmarks
Our take
The rise of generative AI has empowered many industries to fine-tune their operations. PhysicsX utilizes the burgeoning technology to improve the efficiency and advancement of simulations in physics, with applications across aerospace, automotive, renewable energy, medical devices, additive manufacturing, electric vehicles, motorsport, and renewables.
Co-founded by a chief scientist for championship-winning Formula One teams, PhysicsX was born out of a hunger for more advanced research and development phases using numerical physics. R&D and physics simulation go hand-in-hand for many industries, and PhysicsX can help manufacturers iron out problems before they even build a prototype.
Founded in 2020, and raising an impressive $32 million in 2023, the company is pursuing accelerated growth through its customer delivery, product, and research wings. It is about to take the next leap in building out its technology platform and product offering. As it further develops its product, the company has a real chance to capture the market moving forward.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
22% female employees
Company
Employee endorsements
Challenging work
"Inevitably, incorporating cutting-edge AI approaches into the workflows of world-leading scientists and engineers in a way that genuinely enhances..."
Funding (1 round)
Nov 2023
$32m
SERIES A
Total funding: $32m
Company benefits
- Equity package
- Enhanced pension contribution
- 33 days holiday per year with UK bank holidays
- Flexible working (remote-friendly, hybrid)
- Flexible parental leave (3 months)
- Social events (Friday drinks, board game nights, vintage car meet-ups, tech community & art events, etc.)
- 100 hours per year for learning, training, conferences, volunteering
- Bike2Work Scheme
Company HQ
Westminster, London, UK
Articles
Leadership
Jacomo Corbo
(Co-CEO)Previously a Partner at McKinsey & Company, Chief Scientist at QuantumBlack, Senior Research Fellow at Wharton Business School, and Assistant Professor at the University of Ottawa.
Robin Tuluie
(Co-CEO)Previously the Head of R&D at Renault (Alpine) F1, and Chief Scientist and Head of R&D for the Mercedes F1 team.
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