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Tenure Track in Sensory and Consumer Science at Department of Food Science, Aarhus University, De...
is focused on the interface between human senses and perception of food and contribute to designing healthy and sustainable food and beverage applications with high consumer acceptance. The position is
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Network. https://www.eu4greenfielddata.eu/ ***Double Degree PhD Scholarship in Computer Science Opportunity: "Optimization-simulation coupling for the GHG emission estimation based supervision and
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/le doctorant(e) s'investira dans le développement de détecteurs MKIDs. Une forte interaction avec les équipes impliquées dans le projet AMINO est aussi nécessaire afin de bien définir les algorithmes
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for a tenure-track faculty position with knowledge and specialization in one or more of the following areas: user experience design, responsive design, interface design, interaction/web design, motion
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Systems – autonomous vehicles, collaborative robots, and human–machine interaction. · Biomedical Engineering & Health Technologies – wearable devices, brain–computer interfaces, and digital health systems
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departments of physics and 2 departments of chemistry with strong interactions, and gather around 200 members. The candidate will join the STM team within the Surfaces and Interfaces department. The team
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/molecule-surface interactions Where to apply Website https://rubis.univ-spn.fr/offres/voir/202 Requirements Specific Requirements PhD The candidate should have experience in high-frequency-resolution laser
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4-year Group Leader (Assistant Professor) Position in Colloidal Chemistry Related to new ESS Ligh...
across chemistry, biophysics, and food science, and is part of the collaborative framework of the ESS Lighthouse: Colloids and Interfaces in Food and Pharma (CaIFF). The Department of Chemistry at Aarhus
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cortex. Neurobiology of Learning and Memory https://doi.org/10.1016/j.nlm.2021.107525 Defining the sensory neuron response to nerve injury Supervisors: Dr Greg Weir A PhD position is available in
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints