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- Delft University of Technology (TU Delft)
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Field
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of the defining challenges of the coming decade, and it is exactly where this PhD sits. At TU/e you will join the Information and Communication Theory Lab, a group with a long track record in classical coding and
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provides flexibility for the successful candidate to shape the research direction within the broader topic Research Objectives and Contributions RO1: Develop methods for modelling dependencies and cascading
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proven track record of excellence, to work on a challenging PhD project, in an exciting multidisciplinary team. Section Mechanics of Materials The section of Mechanics of Materials (MoM) (www.tue.nl
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distances from the spatial structure of genetic genealogies across the genome, and the genetic relatedness among individuals; or develop and use biophysical models (hydrodynamics + particle tracking
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NTNU and SINTEF. AID brings together academic institutions, research organizations, and more than 50 professional organizations. Its primary objective is to advance AI for decision-making through
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following areas will be highly regarded: High-speed imaging Particle image velocimetry or particle tracking velocimetry Droplet or aerosol size measurement CAD, design for manufacture and rapid prototyping
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
before taking up the position. Research plan; 5-7 pages, where you show your capability to structure a 3-years research study with clear motivation, objectives, research questions, methodologies, expected
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fundamental research, clinical translation, and real-world healthcare impact. With state-of-the-art infrastructure, strong industrial partnerships, and a proven track record of innovation, IBMI offers
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tissue engineering. The objective is to engineer GelMA-based hydrogel matrices, optionally combined with fibrin or rendered porous through phase separation, in order to precisely control their mechanical
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SINTEF, Equinor, and Total. The main objectives of the project include the development and the integration of signal processing and machine learning methodologies aiming to improve flow assurance via field