Research Engineer/Scientist - Machine Learning, Materials Discovery (Contractor)

About Huawei Research and Development UK Limited Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over 170 countries and regions, serving more than three billion people around the world. Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world.

Job Summary: Research and develop AI-driven systems for autonomous materials discovery, with focus on crystal structure prediction and property optimization. Design hybrid world models combining symbolic physics simulators with neural surrogates, and implement LLM-guided search algorithms coordinated through reinforcement learning and Bayesian optimization frameworks targeting accelerated discovery of superconductors, catalysts, and functional materials. Bridge the sim-to-real gap by integrating computational chemistry tools (DFT, molecular dynamics) with autonomous laboratory feedback loops for closed-loop experimentation and model refinement.

Key Responsibilities:

• Conduct original research at the intersection of materials science and machine learning, leading to publications in top conferences and journals (e.g., NeurIPS, ICLR, ICML, Nature Materials, JACS, Physical Review).
• Design and implement algorithms for materials discovery using reinforcement learning, Bayesian optimization, and LLM-guided search.
• Develop and validate world models for materials systems, including hybrid symbolic-neural simulators and surrogate models for expensive quantum mechanical calculations.
• Collaborate with domain experts to translate materials science problems into computational frameworks and validate results against experimental data.
• Actively engage with both the ML and materials research communities through publications, open-source contributions, and cross-disciplinary collaboration.

This job description is only an outline of the tasks, responsibilities and outcomes required of the role. The jobholder will carry out any other duties as may be reasonably required by his/her line manager. The job description and personal specification may be reviewed on an ongoing basis in accordance with the changing needs of Huawei Research and Development UK Limited.

Required:

• Master's or PhD (or currently pursuing) in Materials Science, Computational Chemistry, Chemical Physics, or related field, with demonstrated exposure to machine learning applications.
• Strong foundation in crystallography, solid-state chemistry, or computational materials science (DFT, molecular dynamics, structure-property relationships).
• Familiarity with at least one of the following ML areas: Reinforcement learning, Bayesian optimization, world models, or LLM applications.
• Proficiency in Python and experience with scientific computing libraries and at least one ML framework (PyTorch, JAX, or TensorFlow).
• Ability to work in a fast-paced, research-oriented environment bridging materials science and AI.
• Passion for applying AI to accelerate scientific discovery in the physical sciences.

Desired:

• Publications in materials science, chemistry, or physics journals (e.g., Nature Materials, Advanced Materials, JACS, Physical Review) or at ML/AI conferences.
• Hands-on experience with computational chemistry tools.
• Experience with materials databases and high-throughput computational screening.
• Familiarity with graph neural networks for materials or surrogate modeling techniques.
• Knowledge of autonomous laboratories, robotic experimentation, or closed-loop optimization in physical sciences.
• Active GitHub portfolio showcasing materials informatics or AI-for-science projects.
• Understanding of structure prediction methods (genetic algorithms, particle swarm, basin hopping) and their limitations.