250 learning-"https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Netherlands
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. (2) Prof. Francesca Grisoni (https://molecularmachinelearning.com/ ) leads the Molecular Machine Learning Group at the Technical University Eindhoven and will lead a project on designing potent cyclic
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, enthusiastic and eager to learn, with a strong interest in the research area. You work accurately and meticulously, while being able to work independently as well as as part of a team. You are open to learning
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to work independently and in a team; eager to learn and to develop new (academic) skills; organized, flexible, and have attention to detail. What else do we offer you The position concerns temporary
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Molecular Biosensing and the Protein Engineering research groups at TU/e (see www.tue.nl/mbx and https://merkxlab.nl/ ). Their fields of expertise on continuous biosensing and protein engineering are
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January; multiple courses to follow from our Teaching and Learning Centre; multiple courses on topics such as leadership for academic staff; multiple courses on topics such as time management, handling
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between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; multiple courses on topics such as leadership for academic staff; multiple courses on topics such as time
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Description Welcome to Maastricht University! Do you want to shape how the next generation of Liberal Arts & Sciences students learns to think and act like entrepreneurs and help build the bridge between
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thinker, eager to learn new experimental techniques, and enjoy collaborating with researchers from different disciplines as well as industrial partners. Furthermore, you meet the following requirements: You
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), PURE, for research management, evaluation, and strategic decision-making. This is a learning and decision-support project, not an implementation project. Its objective is to provide university management
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale