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international scientific publications and a dissertation; • presenting findings at national and international conferences; • teaching (10%); • actively participating in the research group
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characterize subsurface structures, buried infrastructure, and material properties; · develop and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction
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layer develops, how it affects heat and mass transfer, and how surface design can improve the efficiency of the process. As a PhD candidate in the Thermal Conversion and Storage group at the University
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cognitive and neurobiological mechanisms of psychopathology. We study clinically relevant processes such as biased information and affective processing, decision-making by patients and clinicians
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vulnerabilities whose manifestations depend on the context. The project aims to develop a nuanced understanding of how ND characteristics related to sensory and information processing, emotion
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engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
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microfluidic channels with a channel wall of low-stress silicon-rich silicon nitride. The proposed research aims to study the fundamentals of bonding glass or metals to silicon nitride coated silicon
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will join BIASlab, a research group in the Department of Electrical Engineering, under the supervision of Dr. Ivana Nikoloska. Dr. Nikoloska is also affiliated with the Casimir Institute. What we're
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usable across domains. The project is embedded in the Computational Geography group at the Department of Physical Geography, where you will work with researchers in environmental geo-spatial AI method
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more computational in nature, this position will lead to publications in law venues. What you will be doing ATLANTIS will be run as a tight team, not as three PhDs working in parallel silos. We will work