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models that significantly accelerate forging process simulations, optimize manufacturing parameters, and reduce dependency on computationally expensive simulations. This position offers the opportunity
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position focused on light-driven CO2 capture. Job description Our group is actively developing a novel photoacid-based approach for efficient CO2 capture, optimizing both the local chemical environment in
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to carry out internationally leading research. Knowledge in one or more of the following topics is sought: engineering design, computational design and optimization, formal languages, engineering design
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. Key Responsibilities: Quantitative in situ and in vitro imaging studies related to cytokine signaling and cell-cell interactions. Design and optimization of multiplexed fluorescence imaging, in situ
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Postdoctoral researcher position on Resilient Energy Infrastructures for the Swiss Energy Transition
modelling and optimization tools developed by FEN researchers. In addition, you will collaborate with researchers from other groups with different scientific background (ICT, machine learning, reliability
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100%, Zurich, fixed-term The modeling of nano-scale devices such as field-effect transistors or memory cells consists of predicting and optimizing the performance of not-yet fabricated components
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from rice straw and rice husks to promote sustainable resource use. Key responsibilities include: Researching material formulations and chemical treatments to optimize panel performance Performing
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of optimization tools. Programming skills in scientific languages such as Python, Julia, Matlab, or GAMS. A strong track record of publications in peer-reviewed journals. Demonstrated ability to work effectively in
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Analyzing experimental data and optimizing protocols This position is full-time, with flexible starting dates in 2025. Profile A PhD degree in physics or relevant fields Prior experience in experimental