PhD: Theoretical Nanoscale Crystal Growth & Modeling

ETH Zürich; Zürich; Vor Ort; CHF 48.000 - 60.000; Vollzeit

Zusammenfassung

ETH Zurich's Optical Materials Engineering Laboratory invites a doctoral student to develop theoretical and computational descriptions of nucleation and growth of semiconductor nanocrystals. Initial focus on CdSe nanoplatelets and magic-sized nanocrystals, expanding to quantum dots and InP.

You will combine DFT energy calculations, mass-balance growth models, and kinetic Monte Carlo simulations, collaborating with experimentalists and using ETH's HPC resources.

Qualifikationen

• Strong background in thermodynamics, kinetics, statistical mechanics, solid-state physics, physical chemistry, or materials modeling.
• Experience with modeling methods such as DFT, kinetic Monte Carlo, and rate-equation solving is advantageous.

Aufgaben

• Develop theoretical and computational descriptions for nucleation and growth of semiconductor nanocrystals.
• Combine models for CdSe nanoplatelets, magic-sized nanocrystals, and quantum dots.
• Extend models to InP and other materials using experimental data for validation.
• Collaborate with experimentalists and utilize ETH Zurich's HPC resources.

Kenntnisse

DFT basics

Kinetic Monte Carlo

Numerical solution

Mass-balance modeling

Materials modeling

Scientific programming

High-performance computing

Ausbildung

MSc degree in chemistry, chemical engineering, mechanical engineering, materials science, physics, computational science or related discipline

Tools

DFT software

Kinetic Monte Carlo

Numerical solvers

Mass-balance modelling

HPC tooling

Jobbeschreibung

ETH Zurich's Optical Materials Engineering Laboratory invites a doctoral student to develop theoretical and computational descriptions of nucleation and growth of semiconductor nanocrystals. Initial focus on CdSe nanoplatelets and magic-sized nanocrystals, expanding to quantum dots and InP.

You will combine DFT energy calculations, mass-balance growth models, and kinetic Monte Carlo simulations, collaborating with experimentalists and using ETH's HPC resources.