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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 6 days ago
The Department of Process Systems Engineering (Director: Prof. Dr.-Ing. Kai Sundmacher) at the Max Planck Institute for Dynamics of Complex Technical Systems is inviting applications for the PhD
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: A completed university degree (Master’s or equivalent) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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in related program areas to gain exposure to and build knowledge on experimental/research activities and approaches, in order to improve conceptual development and industrial implementation. Identify
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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commercialized by a DTU spin-out (Spectroinlets) - but we have to move beyond what we already have in order to enable automated detection of non-volatile products. This will be your main objective. In parallel
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from the chromosome-level reference genome alignments. Historical and population comparisons will also be undertaken. This PhD position will be associated with the Ecology and Animal Science, Production
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, compression, learning, and inference for classical and quantum data. The stipends are within the general study programme Electrical and Electronic Engineering or Wireless Communications, and available from
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populations in order to define sustainable harvest levels. In this PhD position, the candidate will work together with a team of researchers to assess sustainable levels of recreational harvest on willow
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security, aiding conservation and informing management policy. You will use advanced novel genomic approaches to assemble, annotate and explore the genome biology of a non-invasive and one of the most