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, structured PhD program for all doctoral candidates working at LIV with binding guidelines developed based on the Leibniz Association's guidelines for graduate education. Our program offers multidisciplinary
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assistant for a PhD in the field of AI for processing and analyzing text-based data in education Full-time, temporary for 3 years, salary according to EG 13 of the collective agreement for the public service
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implementation science starting October 1, 2025. BIPS, a leading center for population-based research in the heart of Europe, offers the opportunity to pursue a cutting-edge dissertation project. The PhD project
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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with other team members Implement AI-based microscopy image analysis software as python packages Develop algorithms to integrate topology constraints in AI models Report findings and methods in conference and
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Centre for Human Evolution and Palaeoenvironment (SHEP) at the University of Tübingen is seeking a motivated PhD candidate for the Paleontology working group: PhD Candidate / Research Assistant (f/m/d
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Association with an international reputation and globally networked research infrastructure. It is active in three closely interlinked fields: collection-based research, collection development and cataloguing
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Preclinical Metabolomics You will be responsible for Researching oxidative stress within lymph nodes caused by metastatic melanoma Biochemical
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Palaeoenvironment (SHEP) at the University of Tübingen is seeking a motivated PhD candidate for the Paleontology working group: PhD Candidate / Research Assistant (f/m/d)Turtle Neuroanatomy & Evolutionary Morphology
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand