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Position in XAI with Commonsense Knowledge for Robotics and Computer Vision 2. PhD Position in Sustainable AI for Enhancing Health Informatics (Please scroll down to read more about the project descriptions
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Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
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. Collecting and analyzing data from a full-scale (150 kWh capacity) pilot installation at DTU. Developing a computer model (“digital twin”) that link physical experiments with advanced control and operation
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completed each applicant will be notified of the outcome of their application. Closing date: February 01, 2026. The application must be submitted via the electronic recruitment system, using the link below
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characterization techniques such as atomic-force microscopy or scanning electron microscopy. Experience with simulations of photonic nanostructures will also be highly valued. You should have a Ph.D. degree (or
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TEXT Further information Please visit us on LinkedIn: https://www.linkedin.com/company/sdu-robotics . Further information about this position is available via email from Bruno Miguel Gomes Oliveira
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ecology, biology, microbiology, bioinformatics, or a closely related field is an advantage. Excellent oral and written English language skills are a requirement. Previous experience in computer programming
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. Applications should be sent electronically via the link "Apply now". The faculty expects applicants to read the information "How to apply for a position at SDU " before applying. Please note that the application
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than 12 months in the past 3 years. Selection process Applications are accepted only electronically through the application form available at https://efzu.fa.em2.oraclecloud.com/hcmUI/CandidateExperience/en
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basis of your project The application, in English, must be submitted electronically by clicking APPLY NOW below. Please include Motivated letter of application (max. one page) Curriculum vitae Original