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Field
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environment. Excellent communication skills and a willingness to work in an international and interdisciplinary research team. Good command of German or a willingness to acquire German language skills within a
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of AI for next-generation microbiome research? We are looking for a highly motivated researcher to develop novel machine learning and computer vision methods for autonomous live-cell microscopy
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biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we seek The ELBE program seeks
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trials and deep learning-based modeling of multimodal biomedical data. We are seeking two highly motivated scientists with expertise in Causal Inference / Statistics / Deep Learning / Bioinformatics
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exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and
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-based methodologies for protein structure prediction and cofolding Machine learning guided virtual screening Taking on organizational tasks and writing grant applications Your Profile The ideal
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) | Leipzig, Sachsen | Germany | 2 months ago
research on population coding and Alzheimer’s disease Key research methods: fMRI (including 7T), MEG, virtual reality (VR), a wide variety of cognitive tasks, psychophysics, machine learning, deep neural
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
, computer engineering, or a related discipline. Strong motivation, scientific curiosity, and commitment to scientific excellence. Experience in one or more of the following areas: electronics and
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, biomedical engineering, medical technology, optics, mechatronics, computer engineering, or a related discipline. Strong motivation, scientific curiosity, and commitment to scientific excellence. Experience in