Data Scientist

About the role

PhysicsX is seeking a Data Scientist to join their delivery team and help accelerate hardware innovation through physics AI. You will work directly with customers to transform cutting-edge AI models into practical engineering tools. This role involves solving complex problems using data-driven modeling and deep learning techniques in a commercial environment.

Responsibilities

• Pre-processing and analyzing data to prepare it for use in predictive modelling.
• Developing and utilizing innovative deep learning models in combination with state-of-the-art optimization methods to predict and control the behaviour of physical systems.
• Taking full responsibility for the quality, accuracy and impact of your work.
• Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
• Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
• Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
• Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.

Required skills

• Python
• NumPy
• SciPy
• Pandas
• TensorFlow
• PyTorch
• Data-driven modelling
• Deep learning
• Probabilistic methods
• Predictive modelling

Qualifications

• Master's degree
• PhD

Benefits

• Equity options
• 10% employer pension contribution
• Free office lunches
• Enhanced parental leave
• YellowNest nursery scheme
• 25 days of Annual Leave
• Private medical insurance
• Wellhub Subscription
• Employee Assistance Programme
• Bike2Work scheme

About the Company

PhysicsX is the physics AI company for industrials, building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables.