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🎓 Computational Chemistry PhDs

Multi-Scale Computational Framework for Charge Transport and Thermoelectric Properties in Self-Assembled Monolayer Molecular Junctions
Maynooth University Prof. Pierre Cazade 🎓 Biochemistry 🎓 Chemistry Deadline: 01 May 2026

Develop models to predict charge transport and thermoelectric behavior in molecular junctions. Explore nanoscale thermoelectrics for waste heat recovery. Collaborate internationally to bridge molecular design and device…

This research aims to enable rational design of molecular electronic devices, improving nanoscale energy harvesting technologies such as mo…

Charge Transport Thermoelectric Properties Molecular Junctions Self-Assembled Monolayers
e–mides – Amides as Versatile Building Blocks via Reductive Activation
The University of Manchester Dr Giacomo Crisenza, Dr Cristina Trujillo 🎓 Computational Chemistry 🎓 Organic Chemistry Deadline: 04 May 2026

Competition funded PhD at The University of Manchester focused on reductive activation of amides for sustainable catalytic transformations in synthetic organic chemistry.

Pressurised ion transport in nanoporous materials
University of Birmingham Dr Yueting Sun; Prof Zhe Liu 🎓 Computational Chemistry 🎓 Materials Science Deadline: 29 May 2026

Fully funded PhD at the University of Birmingham investigating ion transport in nanoporous materials for energy storage and conversion applications.

Modelling and design of sustainable fibre composites
University of Strathclyde Dr K Johnston 🎓 Chemical Engineering 🎓 Chemical Physics Deadline: 31 Mar 2026

Fibre composites are widely used in aerospace and wind turbines due to their light weight and high strength. This project will use coarse-grained modelling and molecular dynamics simulations to simulate network formatio…

Developing charge-aware machine learning potential for electrochemical applications
Imperial College London Dr Jing Yang 🎓 Artificial Intelligence 🎓 Computational Chemistry Deadline: 31 Mar 2026

This PhD focuses on developing charge-aware machine learning interatomic potentials for electrochemical applications, enabling accurate modelling of electrocatalytic systems with long-range electrostatic interactions.

Mitigating Synthesisability Loss in 3D Generative Models
University of Liverpool Dr Anthony Bradley, Dr Gabriella Pizzuto, Dr John Ward 🎓 Artificial Intelligence 🎓 Computational Chemistry Deadline: 30 Jun 2026

This PhD will combine 3D generative modelling, structural informatics, and chemical insight to tackle a central challenge in modern drug discovery, training researchers at the interface of AI, synthesis, and automation.