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Biomedical Engineering, Mechanical Engineering, Electrical Engineering, Materials Science, or a related field Strong hands-on experience in several of the following areas: Microfluidics (design, fabrication
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experimental research-based technology integration, modeling, control, and data-driven analysis and toolset development. Here is the chance to work in a pleasant team atmosphere, dive into research and at
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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. Key responsibilities include conducting both experimental and theoretical research on the generation, manipulation, and utilization of three-dimensional cluster states for quantum computing
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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solid understanding of energy system technologies and economics is also required. Additionally, experience with other programming languages, open-source software development, project management using
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run simulation experiments across a wide demographic and ecological parameter space Extract genomic metrics from simulated data Contribute to training and evaluating machine learning models
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experience in quantitative modelling, preferably using R. Is fluent in English (spoken and written) and has good communication skills. Is enthusiastic about developing replicable models to address complex risk
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relevant, but not mandatory: Experience and skills within gravity field modelling Programming skills Fieldwork experience GNSS processing Navigation and sensor fusion Quantum gravimetry It is expected
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, sequencing, cell cultivation). Plan, perform, and analyse yeast and immunological experiments independently, driving the project forward (e.g., cellular assays, immunoassays, flow cytometry, cell sorting