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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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prediction Integration of domain decomposition methods into the learning framework to enable efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation
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(Western blot, immunoprecipitation and immunofluorescence) Perform cell culture Develop and optimize protocols for new antibody-based applications Compile data, prepare data figures, and contribute
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and biomolecule release. We are seeking motivated, creative individuals who are interested in conducting hands-on experiments to evaluate and optimize the performance of this technology, including
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. Faculty cover a wide range of research topics and methods and belong to the top 10 ISOM research groups in Europe . You will be able to benefit from the department’s strong research focus and its numerous