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optimization and enable automated diagnosis of performance-limiting factors and suggest optimization strategies. The project will be part of the DFF Sapere Aude project, and research stays abroad are part of
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not exclusively, interested in candidates with competence in data management and data mining, machine learning, large-scale optimization methods, and natural language processing. With a position in
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have practical applications, such as optimizing color selection for attentional purposes. The successful candidate will be required to design, program and conduct EEG-experiments, analyze and interpret
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one of your main responsibilities will be to participate in and help optimize and develop our next-generation sequencing (NGS) workflow. This will include sample preparation either manually or by liquid
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. Derivation of optimal target reliability, incorporating environmental and sustainability considerations Concrete plasticity and limit analysis for structural assessment and safety evaluation. Capacity and
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, current methods are either static, rely on heavy offline training, or fail to adapt to changing environments. This PhD project will develop intelligent software agents capable of autonomously optimizing
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models Develop and optimize advanced protocols (e.g., single-cell assays, CRISPR-based screens) Collaborate with an interdisciplinary network of computational biologists, clinicians, and international
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for the green transition of the energy sector. Our research develops innovative digital tools and methods, combining cutting-edge AI, simulation, and optimization, to create smarter, more resilient, and
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include the following activities: Material development, synthesis and method optimization Metal nanoparticle catalyst and ceramic material and cell component comprehensive characterization and benchmarking
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accumulation in the environment. Recent studies identified natural bio-converters, such as bacteria and fungi that contain efficient PET-degrading enzymes (PETases). These PETases are currently being optimized