Who We're Looking For

As a CFD Simulation Engineering Intern, you will join us over summer 2026 to create the aerospace industry's first comprehensive open-source 3D lifting surface aerodynamic ML benchmark dataset under icing conditions. This exciting opportunity will allow you to build end-to-end simulation workflows for aircraft icing analysis, working with state-of-the-art icing simulation software and open-source CFD tools. Your work will be instrumental in creating datasets that advance how the entire aerospace industry approaches aircraft icing certification and design cycles.

You will gain hands-on experience working at the intersection of computational aerodynamics, ice accretion physics, and machine learning, while contributing to important research that can influence aerospace safety standards. By leveraging open-source CFD and icing simulation packages, you'll help enhance capabilities, reduce costs, and promote innovation in aerospace safety research. Join us in this dynamic role, where your expertise will help establish critical icing simulation capabilities and push the boundaries of innovation in computational aerodynamics!

What You Will Do The intern will engage in the following activities and deliver key milestones throughout the internship:

• Research and evaluate state-of-the-art icing simulation software packages to determine optimal tools for dataset generation and establish simulation best practices
• Design and implement a parametric lifting surface geometry generator using CAD tools to enable systematic exploration of diverse aerodynamic configurations
• Develop a comprehensive Design of Experiments (DoE) framework covering relevant icing conditions, flight conditions, atmospheric parameters, and geometric variations to ensure dataset completeness
• Configure and execute CFD simulation campaigns combining ice accretion modeling with aerodynamic performance calculations on HPC infrastructure
• Create standardized automated data processing pipelines to extract aerodynamic coefficients, pressure distributions, ice shape characteristics, and performance metrics from simulation results
• Research and implement best practices for publishing open-source ML benchmark datasets, ensuring proper formatting, documentation, accessibility, and compliance with community standards
• Collaborate with PhysicsX data scientists and machine learning engineers to structure simulation outputs for training datasets and understand data quality requirements for ML applications
• Prepare comprehensive dataset documentation including methodology, validation cases, usage guidelines, data format specifications, and references to icing physics literature
• Present findings to the team and contribute to potential technical publications and conference presentations
• Develop technical documentation explaining simulation workflows, automation procedures, underlying physics, and optimization strategies

What You Bring To The Table

Required

• Currently pursuing PhD or Masters degree in Aerospace Engineering, Mechanical Engineering, or related engineering field
• Strong foundation in computational fluid dynamics (CFD) concepts, methodologies, and simulation workflows
• Proficiency in programming and scripting languages (Python, Bash, Java) for automation and data processing
• Coursework or demonstrated knowledge in aerodynamics, fluid mechanics, and heat transfer
• Experience with Linux/Unix operating systems and command-line scripting
• Experience in CAD design
• Strong analytical skills with meticulous attention to detail
• Excellent written and verbal communication skills
• Ability to work independently and as part of a collaborative team

Preferred

• Experience building automation pipelines, working with macros, or scripting with CFD simulation software
• Familiarity with ice accretion physics, multi-physics simulations, or aerodynamic performance analysis
• Prior experience with commercial or open-source CFD software packages and visualization tools
• Experience using High-Performance Computing (HPC) environments and job scheduling systems
• Background in parametric design automation, CAD scripting, or mesh generation
• Knowledge of aircraft icing certification standards and aerospace safety regulations
• Experience with cloud computing platforms and parallel computing workflows
• Version control experience and collaborative software development practices
• Interest in machine learning applications for engineering (no prior ML experience required)

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.