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computational approaches, including artificial intelligence (AI), to unravel the mechanisms driving neuroimmunologic diseases. Your responsibilities: Plan and perform innovative large-scale experiments bridging
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for cancer treatment. Your Tasks: Research directions may include, but are not limited to: Investigation of molecular and cellular mechanisms of tumor response to interventional therapies, including
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species Perform bioinformatics and computational analyses to identify microbiome-lifespan relationships Apply rigorous molecular biology methodologies to elucidate mechanisms underlying microbiome effects
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available in the further tabs (e.g. “Application requirements”). Programme Description The Pre-Doc Award offers postdocs and those interested in a doctorate with a very good degree the opportunity to jointly
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number: 2025-0107 We have an open postdoctoral position in the Division “Personalized Medical Oncology” (head: Prof. Sonja Loges MD, PhD). The Department “Personalized Medical Oncology” focusses
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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further opportunities for interdisciplinary training. For more information about the research and study program, visit: https://www.lai.fuberlin.de/en/temporalities-offuture/index.html Job description
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University Munich (www.tum.de). Accordingly, we are currently searching for PhD Students and Postdocs to join our team! PhD Students For PhD students, we are looking for persons that are willing to learn and
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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 hour ago
understanding of the complex physics of the atmosphere with a PhD degree in physics, meteorology, engineering or related fields. Knowledge in one or more of the following: experimental fluid physics and dynamics