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Description Job description Driven by the urgent challenges of climate change and energy security, energy systems are undergoing a paradigm shift toward a fully renewable and power-electronic-dominated future
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include: Full CV, including full publication list (highlight crystal growth experience, add images of grown crystals where relevant) contact information for two references Personal letter of 1 page, where
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(highlight crystal growth experience, add images of grown crystals where relevant) contact information for two references Personal letter of 1 page, where you: describe your background and research experience
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and survival in host cells. Through a combination of microbiology, imaging, molecular biology, and translational modelling, the PhD student will generate data to support the design of biofilm-resistant
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: Fluorescence microscopy and image analysis Expertise in cell culture and molecular biology techniques Experience with additive manufacturing (3D-printing) technology Knowledge of microbiology and cancer cell
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Proteomics unit you will be responsible for data management and infrastructure, implementation and development of analysis pipelines. You will work on different datasets and help our users with image and
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. The techniques used in the project include protein expression and purification, biochemical characterization, and in vitro reconstitution, cell imaging, western blotting, knock-out/down. Working tasks The senior
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), Nouryon (chemically modified fibers and industrial context), and KTH (cross-validation and imaging). Work primarily at Chalmers and the Swedish NMR Centre in Gothenburg, with regular interaction across
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instrumentation for imaging, spectroscopy and in situ experiments. The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies
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data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function