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stakeholder requirements into façade design interventions. Design, prototype and evaluate biophilic façade concepts integrating vegetation, water retention, circular materials and/or habitat-supporting features
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are you going to do Adolescents heavily use synthetic content – AI-generated text, audio, images, and video. However, given their still developing cognitive skills, they may also be least equipped to deal
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. Kindly submit your CV and motivation letter to the attention of Mr. Menno Koeslag, HR Advisor. Where to apply Website https://www.academictransfer.com/en/jobs/364035/phd-candidate/apply/ Requirements
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collaboration between the Molecular Biosensing and the Protein Engineering research groups at TU/e (see www.tue.nl/mbx and https://merkxlab.nl/ ). Their fields of expertise on continuous biosensing and protein
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hiring a doctoral candidate on the subject "Foundation AI models for distribution systems decision-making ". Foundation models have recently emerged as a new learning paradigm in AI. These models learn
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and/or single-cell nucleosome, methylation and transcriptome sequencing. The workflow will be adapted to 3D light-sheet microscopy and thick melanoma samples, addressing challenges linked to image
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), University Utrecht (NL), SciCross (SE), RD –Néphrologie SAS (FR), University of Bern (CH). For more information: https://www.cordis.europa.eu/project/id/101225380 Doctoral project (Promotors: Prof. Dr. Joachim
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developments such as open science, recognition and valorization, and interdisciplinarity, which are firmly embedded in the institute’s strategy. The institute, with approximately 5,000 students and 600 staff
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grow potato plants in the automated phenotyping facilities of the Netherlands Plant Eco-phenotyping Centre (NPEC) external link . Using high-resolution imaging, you will follow plant growth, physiology
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enabled pathway for high value secondary metabolites. By generating and integrating multi-omics, imaging and process datasets, the project will enable AI to (i) accelerate callus line development through