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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
develop our state-of-the-art imaging systems by optimizing the hardware and integrating real-time data processing and analysis through machine learning techniques to achieve precise characterization
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for imaging plant tissues (rose cuttings) Realisation of a corresponding measuring stand and implementation of test series for imaging Realisation of a data processing routine for the automated detection
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Researcher (PhD Position, m/f/d) Neural Circuits and Behavior This position is limited in accordance with § 2 WissZeitVG and § 72 HessHG, offering the opportunity for individual academic qualification and with
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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characterization, clean-room processes or magnetic imaging Past experience in Micromagnetic or Atomistic simulations is desirable, but not mandatory Willingness to work closely with collaboration partners and travel
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for Digital Twins for different agricultural and biorefinery processes Acquisition of third-party funding projects Promotion of bachelor, master and PhD thesis Preparing and publishing research findings in peer
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, the fertilization process. Our research focuses on the physiology and pharmacology of ion channels, employing cutting-edge techniques such as electrophysiology, advanced fluorometric imaging (Ca²⁺, pH, membrane
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer