207 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Denmark
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Anatolia and from the Tigris to the Mediterranean with a focus on visual culture. Qualifications Applicants must hold a PhD degree in Classical Archaeology or closely related disciplines and be able
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
high-impact scientific journals. Your profile The position is offered to a highly motivated candidate with a PhD degree in Soil Science, Environmental Science, Biogeochemistry, Wetland Science, Remote
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biobased processes to promote a green transition and support the UN Sustainable Development goals. Responsibilities and qualifications You will work with a team of scientists including PhD and MSc students
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BSc, MSc, PhD to lifelong learning students. We have about 300 dedicated employees. Read more about us at www.energy.dtu.dk . Technology for people DTU develops technology for people. With our
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. You will join the Junior Innovator program at Aarhus University, comprising young researchers from across all faculties. You will be encouraged to and supported in applying for external funding e.g
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materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300
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cutting-edge experimental and computational technologies. Our aim is to dissect dynamics and cellular programmes active during human blood lineage development and to decipher how haematopoietic
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activities and that you will report research results in high-impact scientific journals. Your profile We are searching for a highly motivated candidate who has A PhD in soil science, digital soil mapping
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are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD students have high academic ambitions and deliver high-quality results for both the private and the public sectors
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: PhD in Veterinary Epidemiology or a related field, or demonstrated experience with epidemiology Strong quantitative data analysis skills Applied understanding of epidemiological principles Demonstrated