Publisher
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ETH Zurich

Doctoral position in theoretical modeling of semiconductor nanocrystal growth ETH Zurich in Switzerland

Degree Level

PhD

Field of study

Chemistry

Funding

Full-time doctoral position at 100% employment for four years. The post is a doctoral candidate role at ETH Zurich; no stipend amount is stated. Access to ETH Zurich high-performance computing resources is provided.

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Country

Switzerland

University

ETH Zurich

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Keywords

Chemistry
Chemical Engineering
Materials Science
Solid State Physics
Model Theory
Density Functional Theory
Quantum Dot
Physics

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About this position

ETH Zurich’s Optical Materials Engineering Laboratory in the Department of Mechanical and Process Engineering (D-MAVT) is recruiting a doctoral candidate for a project on the theoretical modeling of semiconductor nanocrystal growth.

The research focuses on understanding how different growth modes emerge in semiconductor nanocrystals, including CdSe nanoplatelets, magic-sized nanocrystals, and conventional quantum dots, with extension to other materials such as InP. The project combines density functional theory (DFT), mass-balance and rate-equation modeling, and kinetic Monte Carlo simulations to study nucleation, growth, dissolution, morphology selection, and the transition between discrete and continuous growth.

The work is embedded in a highly collaborative environment at ETH Zurich, where theory and experiment are closely linked. Experimental nanocrystal synthesis and stability measurements will inform the models, while simulations will help guide new experiments. The student will also have access to ETH Zurich’s high-performance computing infrastructure and may contribute to teaching and supervision of bachelor’s and master’s students.

Applicants should have, or be close to completing, an MSc in chemistry, chemical engineering, mechanical engineering, materials science, physics, computational science, or a related field. A strong background in thermodynamics, kinetics, statistical mechanics, solid-state physics, physical chemistry, or materials modeling is expected. Helpful experience includes DFT, stochastic simulation, numerical differential-equation solving, atomistic or mesoscale modeling, semiconductor nanocrystals, scientific programming, and HPC. Strong quantitative ability, independence, academic excellence, and fluent English are important.

The position is based in Zurich, Switzerland, is full-time (100%) for four years, and is intended to start on or after October 1, 2026. Applications must be submitted online as a single PDF containing a cover letter, CV, diplomas/transcripts, and at least three references. Questions about the position can be directed to Prof. Dr. David J. Norris at [email protected].

Funding details

Full-time doctoral position at 100% employment for four years. The post is a doctoral candidate role at ETH Zurich; no stipend amount is stated. Access to ETH Zurich high-performance computing resources is provided.

What's required

Applicants must hold, or be close to completing, an MSc degree in chemistry, chemical engineering, mechanical engineering, materials science, physics, computational science, or a closely related discipline. A strong background in thermodynamics, kinetics, statistical mechanics, solid-state physics, physical chemistry, or materials modeling is expected. Experience with density functional theory, kinetic Monte Carlo or other stochastic simulation methods, numerical solution of coupled differential or rate equations, atomistic or mesoscale modeling, semiconductor nanocrystals or colloidal growth, scientific programming, and high-performance computing is advantageous. Strong quantitative skills, academic excellence, ability to work independently, and fluent English communication are required.

How to apply

Prepare a single PDF with a cover letter, CV, diplomas and course transcripts, and contact details for at least three references. Submit the application only through the online application portal; email and postal applications are not accepted.

More information can be found here

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