PHD

How can we accelerate the discovery of next-generation materials - from porous architectures for CO₂ capture to photoactive systems for sustainable solar-energy conversion and unprecedented photomedicines? In this PhD project, you will build a self-driving laboratory platform that will help solving outstanding questions at the forefront of (photo)chemistry by implementing automated spectroscopy workflows for molecular systems and thin films in combination with AI-driven process optimization. Join a highly interdisciplinary project with the spectroscopy at its core at the University of Amsterdam that brings together photophysics, spectroscopy, automation, flow technology and functional materials supervised by a team of passionate experts : Dr Tomáš Šolomek, Dr Bettina Baumgartner, and Prof Tim Noël. The project aims at establishing a self-driving platform based on RoboChem, extending its capabilities to research in porous and photoactive materials. You will first implement new reliable and quantitative diffusion-ordered optical spectroscopy that will permit rapid and automated determination of fundamental photochemical parameters, such as optical spectra, quenching, or quantum yields. This will aid and abet discovery of new systems for photoactivated chemotherapy. Second, you will develop a flow-based ATR-UV-Vis spectroscopy platform that follows the formation of porous or photoactive thin films in real time. By measuring both polarization directions, you will determine how molecular building blocks become oriented during film growth, and how the films respond to external perturbations, such as molecular guests, light or charge. The focus will be on organic cages and metal-organic framework (MOF) thin films as key material classes. The broader goal is to create robust, automated set of spectroscopic tools that connect molecular structure and organization, their properties and function. Join a highly interdisciplinary project with ...

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