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qualifications Responsibilities: Combine enzyme and process engineering supported by machine learning as described above Participate in training events, workshops and secondments within MSCA doctoral network
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The Bernhard Nocht Institute for Tropical Medicine (http://www.bnitm.de/en ) is the largest Research Institute for Tropical Medicine in Germany and is the National Reference Centre for Tropical
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websites. Application Process Applications for both programs must be submitted online by January 14, 2026: https://www.uni-goettingen.de/de/application/556704.html Applicants will be asked to upload a CV
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having
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support, lectures by international experts, and annual PhD symposia. Make sure to see the DTU website to find out more: https://micro-path.uni.lu The Luxembourg Institute of Science and Technology (LIST) is
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student within the field
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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-Holstein (UKSH), is seeking a PhD student with a strong background in statistics, machine learning (ML)/artificial intelligence (AI), or bioinformatics. Our group develops novel computational and statistical
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well as basic research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine:The
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from chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas