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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 5 days ago
, with the possibility of additional one-year renewals. The position is funded by the SFB/TRR 247 collaborative research network “Heterogeneous Oxidation Catalysis in the Liquid Phase” and will be jointly
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focusing on elucidating neural (e.g., EEG/ERPs, MRI), behavioral, and real-time markers (e.g., passive sensor data, EMA) of depression and suicidal behaviors in adolescents. The positions are full-time
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applied research in the domains of food and biobased materials. Where to apply Website https://www.academictransfer.com/en/jobs/364061/machine-learningai-researcher-a… Requirements Specific Requirements You
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monitoring, sensing systems, instrumentation, or transportation infrastructure analytics. Experience working with data-driven technologies such as sensor networks, machine learning, or AI-enabled
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software, analytical platform, chemistry and microbiology laboratories. **Main contacts (CNRS internal and external network):** JH Renault (ICMR), Véronique Eparvier (ICSN), Maria Halabalaki (NPMC, Athens
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for Applied Marine Ecology and Modelling (for more information see: https://ecos.au.dk/en/researchconsultancy/research-areas/applied-marine-ecology-and-modelling). The department is, and wishes to continue to
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specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification
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for this vacancy, this concerns a joint PhD position with KU Leuven as the main institution and primary workplace (and VUB as the partner institution).• Subject-matter expertise and an international research network
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working environment numerous possibilities of career development and advancement cooperation with international partners (extensive network of Erasmus+ partner institutions) canteen, allowance for meals
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be an integral member of the wearables group based at Oxford, led by Aiden Doherty. Our research team has access to world-leading population health data sets with objective wearable sensor measurements