213 algorithms-"Prof" "NTNU Norwegian University of Science and Technology" PhD positions in Germany
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of Tübingen. The project is led by Principal Investigators Dr. Marlen Fröhlich, Prof. Dr. Michael Franke (both Tübingen) and Prof. Dr. Manuel Bohn (Lüneburg). The successful candidate will support the project
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for Structural Systems Biology (CSSB). The Department Virus-Host Interaction (Prof. Wolfram Brune) investigates the interaction of herpesviruses (e.g., cytomegalovirus) with host cells, determinants of cell and
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close cooperation/mentoring with Prof. Dr. Herman Jungkunst and other institutions across Europe, e.g., Ghent University, Belgium or Agroscope, Switzerland. The NitroScope project aims to develop systemic
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cells, Ribo-seq, scRNA-seq, PDX in vivo models. The PhD student will work closely together with a PhD student in the lab of Prof. Michaela Frye, which will focus on the in vivo experiements of the joint
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-Landau in close cooperation/mentoring with Prof. Dr. Herman Jungkunst and other institutions across Europe, e.g., Ghent University, Belgium or Agroscope, Switzerland. The NitroScope project aims to develop
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). Application Procedure Please send your motivation letter, CV, and transcripts of records to Prof. Florian Matthes at matthes@tum.de . Important Notes Severely disabled persons are given preference in the case
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Description The Institute of Systems Biotechnology (Director: Prof. Dr. Christoph Wittmann) stands for excellent research at the interface of biotechnology, systems biology, and sustainable resource
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Universität Leuphana Institut für Management, Accounting & Finance Prof. Dr. Patrick Velte Address StreetUniversitätsallee 1Zipcode21335CityLüneburg Contact details Tel:04131-677-2117 E-Mail: accounting
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Universität Leuphana Institut für Management, Accounting & Finance Prof. Dr. Patrick Velte Address StreetUniversitätsallee 1Zipcode21335CityLüneburg Contact details Tel:04131-677-2117 E-Mail: accounting
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning