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on mountain forest dynamics, and how these can be moni-tored from remote sensing data. Specifically, tasks include: Processing and analysis of remote sensing data Combining remote sensing and field data
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optimization or discrete algorithms. Profound mathematical modeling and programming skills. Experience with the design and analysis of graph algorithms or multiobjective optimization models is a plus. Very good
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-based spatio-temporal interpolation methods • Geophysical interpretation and analysis of the results and impact assessment of past and projected future changes along the coast • Literature research
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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. • Collaborate with project partners. • Contribute to the preparation and analysis of data for publication and presentations. The following qualifications will be of advantage but are not stringently required
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motivated PhD students to strengthen our interactive and collaborative team. The projects are founded on the well-established and highly visible track record of the laboratory in the analysis of plant growth
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tracking T cell tissue entry and exit over time in matched organs by single-cell chimerism analysis. Using multimodal state-of-the-art technologies and specialized high-throughput cell culture methodologies
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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, metal physics, or a similar degree Experience in software engineering (incl. high-throughput computing) Knowledge in the field of materials engineering of metals and materials modelling (i.e. CALPHAD
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biophysical analysis of smart technolgoes, and will involve collaboration with experimental researchers as well as other modellers. There is another PhD position open at the University of Queensland (Australia