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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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substrates while advancing our understanding of deep learning through dynamical systems theory. You will work with two cutting-edge experimental systems: (1) light-controlled active particle ensembles
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Your Job: Reinforcement Learning (RL) is a versatile and powerful tool for control, but often data-inefficient, requiring numerous updates and non-local information such as replay buffers and batch
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interest in one (or two) research projects as part of your application: C01 – Synthesis of organic dyes and redox systems for controlled assembly in mol2Dmat heterostructures (Prof. Eigler, 2 positions
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Tumor Biology – ideally with you on board! Our internationally renowned research team investigates cellular programs of gene control, epigenetics and signal transduction of mammalian cells, with a focus
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Description Reliable monitoring and control of water systems is essential to protect water resources, ensure hygienic standards, and enable sustainable infrastructure operation. As challenges evolve
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 1 day ago
command of English, which is the working language of the department. German is an asset but not required. Our offer We are offering excellent working conditions in a highly interdisciplinary and stimulating
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, chalcogenides, and semiconductor compounds, aiming to understand and control their growth. Analyze the deposited films and structures using scanning probe techniques and other complementary characterization
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funded by the German federal government and 10 percent by the state of Berlin. Job Description Our laboratory investigate how the nervous system processes sensory information to orchestrate motor behaviour
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, using techniques such as: High-dimensional data mining Tensor decomposition Causal inference Statistical process modeling Machine Learning Applications include public transport, private vehicles, traffic