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the time you start (you can apply before they are met e.g. during your PhD). A doctoral degree (PhD or equivalent) in an area relevant to the announcement. Everyone is welcome to apply but due to regulations
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will focus on the prediction of genetic interaction networks and image analysis for automated phenotyping. We welcome interest in developing both ongoing and novel research projects in the lab, and are
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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, and use deep learning to gain insight into biological processes. You will also gain direct exposure to cardiovascular physiology and rodent imaging in close collaboration with biologists. We work
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with the attributes listed in the requirements section are strongly encouraged to apply. Education Requirement: PhD or equivalent in psychology, neuroscience, cognitive science, biomedical engineering
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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vulnerability or survival during neurodegenerative conditions in vivo. Responsibilities of the postdoc will include, but are not limited to: in vivo imaging of biosensors to read out diversity and dynamics
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pioneering solid-state CPL spectrometer (Nat. Commun., 2020, 11, 1676) triggered a paradigm shift in CPL spectroscopy that has been hindered over the last 50 years due to its stagnant design that prevented its
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Description of the AMBER project This post-doctoral position is part of AMBER, Advanced Multiscale Biological imaging using European Research infrastructures, which will address scientific and sectoral gaps in
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format: Motivated letter of application (max. one page). CV incl. education, experience, language skills, publication list and other skills relevant for the position. PhD and Master diplomas and transcript