21 phd-image-processing-"Multiple" Postdoctoral positions at Chalmers University of Technology
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. Within the division, the Kádár Group conducts research in the broader field of rheology and processing of soft matter. Our ongoing projects center around three main areas: Field–matter interactions
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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of Technology to pioneer the next generation of biorefineries using marine and terrestrial biomass. This postdoctoral position offers the opportunity to develop innovative green processes for transforming
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models into Chalmers’ bridge simulators in collaboration with other researchers. You are also expected to supervise PhD and MSc students and to publish at least two peer-reviewed journal articles during
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of the Wallenberg Centre for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing
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electromagnetic processing. The work involves close cooperation across several departments. You will have access to a well-equipped experimental environment and be part of a collaborative team dedicated to creating
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focuses on the development of new materials and processes for electronics packaging and bioelectronics applications. The research of the electronics packaging group in the Electronics Materials and Systems
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Are you passionate about advancing lithium-ion batteries and driving innovation in next-generation batteries? Do you want to transform advanced electrode processing for electric vehicle batteries
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edge research in materials design, processing, and advanced characterization. We promote interdisciplinary collaboration and sustainability focused research, with strong ties to both academic and
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC