135 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions at Nature Careers in Denmark
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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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characteristics. The insight will be used to assess global deep sea carbon turnover in the past and presently. Experience in lipid biomarker analysis, microbial cultivation, statistical modelling or machine
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming
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collaborate with experts in machine learning, immunology and microbiology. You are expected to work independently and coordinate your research with the other team members. Undergraduate research projects will
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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sedimentary archives, to facilitate and use in-situ and remote sensing observations of polar environments, and to acquire skills within VibroSeismic data acquisition, analysis and interpretation. The position