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, susan.hartmann(at)tropos.de , +49(0)341-2717-7489 By sending the application documents by e-mail, the applicant agrees to the storage/processing of personal data in accordance with Art. 13 DSGVO for the purpose
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, susan.hartmann(at)tropos.de , +49(0)341-2717-7489 By sending the application documents by e-mail, the applicant agrees to the storage/processing of personal data in accordance with Art. 13 GDPR for the purpose
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) according to Article 13 and 14 GDPR on data protection processing during the application process: https://www.ipb-halle.de/en/career/data-protection-information-for-applicants/
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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well as willingness to take part in the organisation and execution of field expeditions at sea are required. Experiences with data processing and visualization are advantageous. We expect very good English language
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Foundation (DFG). This PhD project is dedicated to numerical modelling of WMT processes in the Skagerrak by applying Eulerian and Lagrangian analysis methods to quantify the mixing responsible for the WMT
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submitted electronically no later than the 15th of June 2025 and be addressed to recruiting@senckenberg.de quoting the reference number 10-25005. For data protection information on the processing
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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at: https://www.ipb-halle.de/institut/ Data protection: Please note the data protection information for applicants (m/f/d) in accordance with Art. 13 and 14 GDPR on data processing in the application process
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of traits such as visual anther extrusion, heading date, plant height, and grain yield. You process genotypic data, ensure its alignment with phenotypic data, and conduct association analyses to identify