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Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software. Develop flow cells to connect various spectroscopic tools to the setup. Create and
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professors, two postdocs, and five PhD-students. The group focus on high-quality applied research. The current topics of interest in the group include student learning, transitions and career, teacher
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influencing factors and improve the accuracy, robustness and energy efficiency of intelligent sensing systems. Apply AI as an engineering tool: Use signal processing, statistical methods and machine learning
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goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include the development
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flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT
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), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development
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chemistry and study the physicochemical properties of peptides loaded into the materials. Build surrogate models and apply machine learning techniques to extract design rules and rapidly screen thousands
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in the design and development of the detector upgrade. The LPC is also a major hub for Machine Learning and AI developments for particle physics. There is close and frequent collaboration with
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student and postdoc who will carry out experimental work, which will allow for validation of the models. You will collaborate with experts from TU Delft, TNO and several large and SME companies involved in
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applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). An engineering degree, preferably, aerospace or mechanical