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Campus (LLEC). Development of physics-informed and graph-based machine learning methods for energy system monitoring, forecasting, and planning Data analysis considering uncertainties, missing data
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systems in a targeted manner. Learn more about us at www.biosystem.design An integral part of BioSysteM is the AI Core Unit, a cross-institutional support unit. This unit aims to make machine learning (ML
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-cell imaging, multi-omics profiling such as transcriptomics, proteomics, and metabolomics, single-cell and spatial analyses, multiplex biomarker quantification, functional studies, machine learning
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looking for a PhD candidate to work on research at the intersection of machine learning, data privacy, and medical imaging. The position is part of a three-year research project that investigates how
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diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy communication, and policy brief writing
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Heidelberg, Baden W rttemberg | Germany | 3 months ago
Cooperation Unit (CCU) Applied Tumor Immunity is seeking, as of September 2026, a Doctoral Researcher – CAR T Cell Therapy Development Reference number: 2026-0131 The immune system influences the efficacy
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Science in Earth Observation develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth
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European Molecular Biology Laboratory (EMBL) | Brandenburg an der Havel, Brandenburg | Germany | about 2 months ago
machine learning/AI with modern biology at the AI Hub Heidelberg as part of EMBL AI, a major institutional initiative to embed AI across all areas of life sciences. EMBL provides a unique environment for
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to design and control biological systems in a targeted manner. An integral part of BioSysteM is the AI Core Unit, a cross-institutional support unit. This unit aims to make machine learning (ML) and
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Master's degree or PhD in Biostatistics, Data Science, Machine Learning, Bioinformatics, or a related field. Experience with genomic data (e.g., Whole Genome Sequencing, 16S rRNA sequencing, single-cell RNA