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include but are not limited to: · Computational / algorithmic genomics · Algorithms and data structures for statistical inference over biological data · High/super
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redox balance. Our studies explore how p53 integrates metabolic cues by acting as both a sensor and regulator of cellular metabolism. In parallel, we are identifying metabolic changes that promote tumor
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bioprinting, regenerative medicine) to in vitro and in vivo biomedical engineering (in vivo sensor technology, in vivo physiologic monitoring, in vivo pharmacies) to AI-driven imaging and mathematical modeling
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channels, cellular signaling, animal disease modeling, molecular sensors, and optical methods. We especially welcome applicants focused on neural circuits, synaptic physiology, genetic underpinnings
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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investigate new algorithmic principles that make learning agents adapt to non-stationary environments in an autonomous manner. The expected outcomes are new theoretical insights about the algorithmic roots
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the necessary algorithms. You will also develop and document a graphical user interface which handles large processing tasks efficiently and uses multiprocessing and GPU acceleration where necessary. At the same
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on Fragmentation in Star-forming Cores Quantum Plasmonic Sensors If you have obtained your PhD (or equivalent) within the past three years - or expect to complete your PhD within six months of appointment* - you are
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to work on new image processing algorithms for cryo-EM structure determination in our open-source software RELION. In particular, we are aiming to improve its core refinement routines through exploration
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well as the processing and publication of multimodal sensor data. Scientific design and definition of measurement strategies for two-stage thermographic inspection (passive and active) inside rotor blades Selection