10 critical-discourse-analysis Postdoctoral positions at Chalmers University of Technology
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at the Division of Systems and Control, Department of Electrical Engineering at Chalmers University of Technology. Project description Lithium-ion batteries are critical for electrified transportation and smart
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Parkinson. We use in vitro biophysical analysis to characterise protein aggregates and their formation in combination with advanced live cell fluorescence imaging and cell model development to study protein
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postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
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to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
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). This position offers a unique opportunity to collaborate closely with researchers across the Division of Marine Technology at Chalmers University, with a focus on maritime transportation risk analysis. Project
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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), recovery of critical raw materials, and the synthesis of new materials from secondary sources. More information about the research can be found here: Industrial Materials Recycling – Chalmers Main
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biomass characterization, biomaterial characterization and application. Experience in glycomic analysis is highly recommended. Laboratory experience in biomass transformation in materials and water based
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This postdoc project aims to address a critical challenge in quantum computing: errors in superconducting qubits caused by cosmic radiation, which cannot be corrected using existing methods
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applications, specifically targeting the prognosis and risk prediction of Heart Failure (HF) in patients. This research integrates AI safety, explainability, and multimodal medical data analysis to enhance