59 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions at Technical University of Munich in Germany
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embedded into the quantum technology network formed by WMI, the Excellence Cluster MCQST (www.mcqst.de), the TU München (www.tum.de), Munich Quantum Valley (https://www.munich-quantum-valley.de/), and many
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Technology Chair of Theoretical Information Technology Theresienstrasse 90, 80333 Munich https://www.ce.cit.tum.de/en/lti/team/boche/ The position is suitable for disabled persons. Disabled applicants will be
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Technical University of Munich School of Computation, Information and Technology Chair of Theoretical Information Technology Theresienstrasse 90, 80333 Munich https://www.ce.cit.tum.de/en/lti/team/boche
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on developing the imaging system as well as novel machine learning approaches for image analysis and disease classification using field data from German and Brazilian agricultural trials. Responsibilities Design
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. Contact details of at least two references. All the other positions offered by COMBINE can be found in https://euraxess.ec.europa.eu/jobs/401249 The position is suitable for disabled persons. Disabled
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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: Prof. Dr. Antonella Di Pizio (a.dipizio.leibniz-lsb@tum.de). More information on the working group can be found here: https://www.leibniz-lsb.de/forschung/forschungssektionen/sektion-iii. Please send
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understanding of immunology and the central nervous system • Very good written and spoken English • Analytical and creative mindset, with a strong willingness to learn new techniques Desirable experience • FELASA
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or similar • High level of self-motivation to achieve a doctorate • Analytical, creative and solution-oriented mindset • Strong interest in familiarising yourself with new topics and learning complementary