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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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Max Planck Institute for Biology Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 21 days ago
once a year to meet with the consortium. The position is for two years, with the possibility for extension. Requirements PhD (or equivalent international degree) or enrolled in a PhD degree program (or
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own simulations) identification of critical biogeophysical Earth system processes and feedbacks that shape planetary resilience coordination with the other scientists in the PB-TIP project, within
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resonance. Your tasks are among others: Operation of a millikelvin scanning probe microscope Investigation of molecular and atomic spin/qubit systems on surfaces using spectroscopic techniques Fabrication and
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, you must have a PhD in a relevant field. As a suitable candidate, you have expertise in deep convective cloud processes and experience with scientific data analysis. Prior experience in applying machine
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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own simulations) identification of critical biogeophysical Earth system processes and feedbacks that shape planetary resilience coordination with the other scientists in the PB-TIP project, within
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Contract:TV-L Your tasks The available research projects aim to understand and develop strategies to treat heart disease You will combine epigenetic, chromatin interaction analysis and single-cell approaches