11 assistant-professor-computer-science-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr" PhD positions at Leibniz in Germany
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formal master’s degree programs (or equivalent) qualifying for a PhD program in epidemiology, statistics, and prevention and implementation science/public health, or to have completed such a program by
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Pathogens, a WHO Collaborating Centre, and a member of the Leibniz Research Association. The Computational Infection Biology Department, led by Thomas Otto, is seeking a highly motivated PhD Student (in data
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://www.ipb-halle.de/en/ ). Contact details: We are looking forward to receiving your online application https://ipb-halle.mhm.jobs/jobs/10-phd-position-in-biology-m-f-d-1-2026/job_application/new For informal
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- Integrating exudation into the root economics space to better understand carbon and nutrient cycling in managed grasslands” is part of the DFG Priority Program 1374 “Biodiversity Exploratories”. The project
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program. Requirements Very good master's degree in computer science, data science, mathematics or a related discipline; relevant research experience (e.g., master's thesis) in the field of NLP/ML/text
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personal skills. Candidates ideally combine several of the following skills and qualifications: A very good M.Sc. degree (or equivalent) in biology, physics, computer science, maths or a similar field A
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The German Primate Center (DPZ) - Leibniz Institute for Primate Research in Göttingen conducts basic research in primate biology, molecular biomedicine and neuroscience. It maintains four field
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research project, and the training programme is available on the RTG webpage (https:// www.uni-goettingen.de/rtg2906). Applications are due by 15.01.2026. We ask you to submit your written application as a
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tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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collaboration with partners at the Robert Koch Institute (RKI) and other Leibniz institutes. It combines bacterial cultivation, molecular biology, and microbial genomics to better understand the transmission risk