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this pathogen to cause infections, survive attacks by innate immune cells (macrophages and neutrophils), and develop resistance to antifungal agents (see selected publications below). The PhD student will learn
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-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical
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models of cellular dynamics are expressive enough to map any source to any target state, but they fall short of learning the underlying regulatory principles. We work on regularization, training on time
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, link ecological and EO data, and integrate your findings into models to predict ecosystem functioning in response to global changes and management interventions. You will learn how to publish your
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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numerous opportunities to exchange ideas with other doctoral students, receive feedback on the work in progress, and acquire the skills necessary for an academic career. The Doctoral Program also supports
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system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing, and machine-learning-based analytics. The research work at NTNU will focus particularly
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machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials