Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

PhysicsX is seeking individuals to join their deep-tech company, which is accelerating hardware innovation using AI-driven simulation software. The role involves applying machine learning techniques to solve complex problems in materials science and computational chemistry, with opportunities to influence research workstreams and contribute to production-ready pipelines.

Responsibilities

• Work closely with a multi-disciplinary team to employ and advance state-of-the-art machine learning techniques for materials problems.
• Develop and apply machine learning interatomic potentials (MLIPs) to model atomistic systems.
• Design and run experiments on large-scale chemistry and materials datasets, iterating on model architectures.
• Own research workstreams from model development through to evaluation on real-world materials problems.
• Collaborate with the broader research team to ensure models are robust, reproducible, and translatable into production-ready pipelines.
• Work on high-performance computing infrastructure for atomistic simulations and generative modelling.
• Communicate work internally and externally through publications, workshops, and customer conversations.
• Mentor colleagues with less experience in computational chemistry or materials ML.

Requirements

• Enthusiasm for applying machine learning to real-world materials science and computational chemistry challenges.
• Ability to scope and effectively deliver research projects, balancing rigour with pragmatism.
• Strong problem-solving skills and ability to translate materials or chemistry challenges into computational formulations.
• Excellent collaboration and communication skills with research colleagues, engineers, and customers.
• Hands-on experience in using and fine-tuning at least one MLIP backend (e.g., MACE, FAIRChem/OCP) and integrating it into larger computational frameworks.
• Direct experience with established chemistry and materials benchmark datasets (e.g., OC20, OC22, Materials Project).
• Proficiency in Python.
• Experience working in high-performance computing environments.
• Experience contributing towards a large multi-module codebase.
• Experience with generative models, preferably applied to molecular or materials systems.

Skills

• Machine learning
• Materials science
• Computational chemistry
• Machine learning interatomic potentials (MLIPs)
• Python
• High-performance computing (HPC)
• Generative models

Location

• Shoreditch office

Work Type

• Hybrid

Experience Level

• Multiple levels and positions
• PhD

Education Level

• PhD in computational chemistry, physics, materials science or a closely related field.

Benefits

• Equity options
• 10% employer pension contribution
• Free office lunches
• Enhanced parental leave (3 months full pay paternity, 6 months full pay maternity)
• YellowNest nursery scheme
• 25 days of Annual Leave (+ Public Holidays)
• Private medical insurance (100% employee cover)
• Wellhub Subscription
• Eye tests
• Personal development support
• Employee Assistance Programme (EAP)
• Bike2Work scheme
• Season ticket loan
• Octopus EV salary sacrifice

About the Company

• 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.
• Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

Equal Opportunity

• 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.