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for robotics, perception, prediction Computer vision and data acquisition System modelling and control JUNIOR RESEARCHER – Responsibilities Participate in R&D tasks across ongoing projects Support experimental
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for robotics, perception, prediction Computer vision and data acquisition System modelling and control SENIOR RESEARCHER / LABORATORY LEADER – Responsibilities Lead one of the robotics laboratories (assignment
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interpretation of climate model outputs Profile of the graduate The graduates of the ‘Physical Geography and Geoecology’ doctoral study programme have advanced knowledge and skills in their chosen specialization
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to the biological model, presentation and publication of the results achieved on an international level, involvement in the preparation of related national and international projects, participation in key project
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of immunocompetent cells), whole organisms (transgenic animal models are often used here) and communities (frequency of different alleles of genes regulating the immune response, evolution of immune mechanisms
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myeloid leukemia (DSPII) Control of chromosome segregation during early development in mammals Development and characterization of a pig model for the study of Usher syndrome type 2C (USH2C) From Signal
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or accepted). Experience with morphometric analysis, climatic niche modelling and/or significant fieldwork experience in tropical mountains is advantageous. Benefits: 5 weeks of paid holiday yearly, subsidized
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, field ecology, mathematical modelling, etc.) and a combination of analytical and holistic approaches to problem-solving. Core facilities with shared equipment support all research groups. About the
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in fluorescently labelled SecYEG complex reconstituted into model lipid systems. In the framework of the ITN project, Ph.D. student will undergo 2 secondments at Johannes Kepler University, Linz
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generating electron-positron pairs through the collision of structured laser pulses. As a PhD student, you will work at the interface of plasma physics, quantum electrodynamics, and computational modeling