49 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Munich in Germany
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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not
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of Computation, Information and Technology (CIT), located on the Garching Campus, starting October 01, 2025 or later. The group is seeking a highly qualified candidate for a postdoctoral position who possesses
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the following areas: PhD in mechanical/electrical engineering, robotics, computer science, or a comparable field, Experience in self-reliant managing of research projects (financial and administrative) and
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We
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to 5 and more years. Requirements: • You have a PhD degree (or postgraduate degree MSc) in a computational discipline, preferably with significant experience in Bioinformatics or Computational Biology
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to contribute to groundbreaking work in our research area. About the Program: We are implementing a program that creates an additional two year postdoctoral position exclusively for female researchers working in
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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engineering, computer science or electrical engineering, with good grades. Experience in scientific work, project proposal writing and team leadership are part of your repertoire. In addition, you are
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requirements: • PhD diploma in related field • Excellent skills in statistical analysis • Very good knowledge of English; spoken German is a benefit • Excellent scientific and writing skills Who we are: You will
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal