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The Laboratory of Cortical Information Processing | Vision to Action at NERF (www.nerf.be ) invites applications for a PhD student to join a Simons Foundation-funded, collaborative research
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for renewable fuel production. Reference notes can be found here . PhD Scholarship details Funding: $37,440 per annum (2025 rate) indexed annually. For a PhD candidate, the living allowance scholarship is for 3.5
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The Laboratory of Cortical Information Processing | Vision to Action at NERF ( www.nerf.be ) invites applications for a PhD student to join a Simons Foundation-funded, collaborative research
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the communicative and emotional demands of social interactions using a multidisciplinary, cognitive neuroscience approach. We are seeking two highly motivated PhD candidates to join our interdisciplinary research
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Published Wednesday 28 May 2025 Deadline Sunday 22 Jun 2025 Work area PhD Organisational unit Erasmus School of Health Policy & Management (ESHPM) Salary € 2.901 - € 3..707 Employment 1 fte - 1 fte
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Description Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI ( baiome.org ) to complement our lively and enthusiastic team of machine learning and data analysis experts. The main tasks include the analysis of complex biomedical data using...
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CoSi project (Co-Evolution and Coordinated Simulation of the Swiss Energy System and Swiss Society), we are seeking a motivated and qualified PhD candidate to develop neighbourhood- and district-scale
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PhD in Aneuploidy in Mammalian Embryos / Clinical Veterinary Embryologist Faculty: Faculty of Veterinary Medicine Department: Department Clinical Sciences Hours per week: 36 to 40 Application
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? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase. Your work will help shape environmentally
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust