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developing approaches to leverage spatial data to better understand evolutionary histories. More information about the lab and their work can be found by visiting https://federlab.github.io/ About the
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, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree. More about being a doctoral student at LTH on lth.se. https://www.lth.se/english/study-at-lth/phd-studies
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We seek a PhD-holding research enthusiast, with an interest in developing high-impact research modeling
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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comprising computational biologists, bioengineers, and immunologists. The candidate will have access to advanced platforms for single-cell and spatial omics, 3D tissue modeling, bioreactors, and in vivo models
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test a conceptual SDI model for integrating heterogeneous (conventional geospatial, environmental, behavioural, and human-centred) datasets, including qualitative and quantitative data, across spatial
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. The objective is to combine ultra-high-precision spatial localization, reduced acquisition times, and access to key photophysical parameters enabling characterization of the local environment of fluorophores
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will be used to ground-truth model outputs, refine risk indicators, and assess the effectiveness of adaptive forest management strategies. Your background We are looking for a person with a PhD in
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will commence on October 15, 2024. Applicants should hold a PhD in Computer Science or a related technical field on or before October 1, 2024. The project focuses on conducting cutting-edge research in
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. • Design and implement studies on themes such as recreational quality, mental well-being, social connectivity, and resilience—integrating geospatial and spatial-temporal analysis to assess patterns