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Apply now Are you passionate about the future of education and AI? Join us as a PhD candidate to explore how adaptive AI can enhance innovative teaching and learning. This interdisciplinary project
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depth. You organise your work efficiently, take initiative, and are able to work independently when needed. You’re open to feedback and eager to learn from it, and you enjoy collaborating within
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significant controversies regarding the exact mechanism of action. To understand the molecular and biophysical principles of protein folding, we aim to build fully controllable chaperone-like machines using DNA
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scientific programming and numerical / statistical analysis of simulated and observed data. Candidates should be able to demonstrate motivation and a strong eagerness to learn, and have the ability to both
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data (e.g., Instagram and TikTok activity) from youth, to be able to gain unique insight into what they post and consume online. This proposed PhD project will form an integral part of a larger
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observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation
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motivation to learn, cryo-EM data collection, image processing, and 3D structural analysis. Prior experience with cryo-EM single-particle analysis (SPA) and/or cryo-electron tomography (cryo-ET) is a strong
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challenges and opportunities (or willingness to learn) has understanding of benefit sharing in payment for ecosystem services (or willingness to learn) preferably has fieldwork experience (in the Global South
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excellent English oral and writing skills and willingness to learn Dutch. Our offer A position for 1 year, with an extension to a total of 4 years upon a successful assessment in the first year, and with
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them further with the help of your supervisors’ feedback. You are willing to teach for part of your contractual working hours. You have earned a university bachelor and master degree, or an equivalent