Research Associate, AI-Driven Materials & Tribology

University of Sheffield; Sheffield; Presencial; GBP 42.000 - 54.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

38 days annual leave

Pension scheme

Discounts at shops/cinemas

Cycle to work

Development and mentoring programs

Wellbeing support

Descripción de la vacante

University of Sheffield invites applications for a fully funded 39-month position in Surface engineering & tribology for silicone-free consumer products. You will develop explainable machine learning models to decode polymer-solvent thermodynamics and map soft-matter physics to real-world applications.

Candidates should hold a PhD (or near completion) in a relevant quantitative field and have programming experience (Python, Julia, or C++) with Git for version control.

Formación

• PhD in computational chemistry, cheminformatics, physics, chemical engineering, applied mathematics, computer science, or closely related quantitative discipline.

Responsabilidades

• Develop explainable ML models (symbolic regression, Bayesian optimisation, genetic algorithms).
• Featurise complex polymer architectures for ML models and analyse multi-modal datasets.
• Create open-source cheminformatics tools in Python/Julia for design and discovery.

Conocimientos

Python

Julia

C++

Git

Machine learning

Educación

PhD or near completion in a quantitative field

Herramientas

Open-source cheminformatics

Python/Julia for scientific computing

Descripción del empleo

University of Sheffield invites applications for a fully funded 39-month position in Surface engineering & tribology for silicone-free consumer products. You will develop explainable machine learning models to decode polymer-solvent thermodynamics and map soft-matter physics to real-world applications.

Candidates should hold a PhD (or near completion) in a relevant quantitative field and have programming experience (Python, Julia, or C++) with Git for version control.