Overview
In this PhD role you will develop theoretical and computational descriptions of nanocrystal nucleation and growth. You will integrate DFT, mass-balance modeling, and kinetic Monte Carlo to explain growth modes across nanoplatelets, magic-sized nanocrystals, and quantum dots. The work combines theory, computation, and experiment to guide synthesis toward better control of size, shape, and optical properties. You will collaborate with experimentalists, use ETH's HPC resources, and contribute to teaching and mentoring, within a collaborative, international lab culture.
Leistungen / Benefits
- collaborative international group
- training across multiple modeling approaches
- access to advanced computing facilities
- interaction with experimental scientists
- opportunities to present at international conferences
- supervision of student research projects
Verantwortungsbereiche
- Develop theoretical and computational models for nucleation and growth of semiconductor nanocrystals
- Apply DFT to obtain surface, edge, and defect energetics to parameterize growth models
- Create mass-balance models for coupled growth/dissolution of nanocrystal populations and compare with experiments
- Extend models to include quantum dots and different materials (e.g., InP)
- Perform kinetic Monte Carlo simulations of early growth stages to study morphology selection
- Collaborate closely with experimentalists to integrate data and guide experiments
- Utilize ETH's high-performance computing resources for simulations
- Contribute to general lab activities and participate in teaching/supervision of students
Zentrale Anforderungen
- MSc degree in chemistry, chemical engineering, mechanical engineering, materials science, physics, computational science, or closely related discipline
- Strong quantitative foundation in thermodynamics, kinetics, statistical mechanics, solid-state physics, physical chemistry, or materials modeling
- Ability to work independently and communicate fluently in English
- Interest in applying theoretical and computational methods to materials growth
- curious and self-driven
- strong communication and collaboration
- professional approach to research
- Density functional theory and electronic-structure calculations
- Kinetic Monte Carlo or stochastic simulation methods
- Numerical solution of coupled differential or rate equations
Doctoral position in theoretical modeling of nanocrystal growth in Zürich Arbeitgeber: ETH Zürich
ETH Zürich ist ein hervorragender Arbeitgeber, der Ihnen die Möglichkeit bietet, aktiv an der Gestaltung der Zukunft des Forschungsdatenmanagements mitzuwirken. Mit einem interdisziplinären Arbeitsumfeld, attraktiven Beschäftigungsbedingungen und zahlreichen Vorteilen wie Kinderbetreuung und öffentlichen Verkehrsmitteln fördert ETH Zürich nicht nur Ihre berufliche Entwicklung, sondern auch eine inklusive und nachhaltige Unternehmenskultur. Hier haben Sie die Chance, in einer sichtbaren Position mit hoher Verantwortung zu arbeiten und einen bleibenden Einfluss auf die Forschung zu nehmen.
