About us
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Please only apply to one internship position you feel most aligned with.
If we think you are better suited for another, we will communicate this to you.
Our internship opportunities are designed for students who want to apply what they’ve learned in their degrees to real engineering problems. You’ll work alongside simulation engineers, data scientists, machine learning engineers and research scientists on our projects, gaining hands-on experience and insight into how physical AI is developed and used in industry.
Who We're Looking For
Our team has established strong foundations at both ends of the length scale spectrum, utilizing Density Functional Theory (DFT) models in conjunction with continuum-scale simulations. This internship will focus on enhancing our capabilities at the meso-micro scale, creating more robust and direct coupling between modelling approaches.
The intern will work specifically for hierarchical material systems, developing:
- Continuum-scale models based on ASTM procedures to establish digital twins for tensile and fatigue testing
- Microscale models to evaluate ply stacking sequences, with computational outputs serving as direct inputs to continuum-scale models
- Optimization frameworks to determine optimal stacking orientations for specific material testing procedures
What you will do
The intern will engage in the following activities and deliver key milestones throughout the internship:
- Establish continuum-scale modelling framework by configuring ASTM-compliant testing procedures (tensile and fatigue) using existing CalculiX pipelines
- Develop microscale stacking sequence models in NASMAT to simulate ply orientation effects and mechanical behaviour at the micro-structural level
- Create automated coupling pipeline to seamlessly transfer stacking sequence computational outputs from NASMAT as direct inputs to CalculiX continuum-scale models
- Train and calibrate multi-scale models using available literature benchmarks to ensure accuracy and reliability across length scales
- Implement optimization algorithms to evaluate and identify optimal stacking sequences for various load cases and material testing scenarios
- Validate computational framework by comparing results against published literature and quantifying potential reduction in required physical tests enabled by the modelling approach
- Document methodology and results in technical reports detailing model development, validation procedures, and recommendations for future applications
- Present findings to the engineering team, demonstrating the capability and efficiency gains achieved through the coupled multi-scale modelling approach
These responsibilities will provide hands-on experience with industry-standard computational tools, multi-physics coupling techniques, and optimization methodologies while contributing directly to advancing our ICME capabilities.
What You Bring To The Table
- Currently pursuing a PhD (or Masters) degree in Mechanical Engineering, Civil Engineering, Aerospace Engineering, or a related field.
- Familiarity with Integrated Computational Materials Engineering (ICME) methodologies and multi-scale modelling approaches
- Hands-on experience with any of the open-source numerical simulation platforms such as CalculiX, MOOSE or FEniCS and material modelling framework such as NASMAT
- Proficiency in programming or scripting languages (e.g., Python) is mandatory.
- Comfort working in Linux/Unix environments and experience with high-performance computing (HPC) systems
- Exposure to optimization algorithms and their application to engineering problems
Salary:
The estimated range for this position is $45 - 55 USD per hour. The total compensation will be determined by each individual's relevant qualifications, skills and work experience.
Applications will close 10 February 2026.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
Salary :
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