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Are you interested in designing innovative separation methods that use an electric field as an additional driving force? Can you combine experimental with simulation results into a design that is
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requirements You hold an MSc degree in Electrical Engineering (must-have). You have a strong interest and demonstarted interest in analog integrated circuit design Hands-on experience in circuit design, gained
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sectors. Process driven research activities are performed in the field of chemical and biochemical systems, mechanical and electric systems and system networks. Typical product sectors include biobased
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, you will: combine knowledge on electrostatic interactions, fluid dynamics and machine design; design a novel, scalable, separation process for proteins that uses electric fields as a driving force
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Interaction trains professionals who already have a Master’s degree in design or engineering to develop competencies in designing and evaluating interactive, intelligent, and innovative systems, services, and
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)design; integrating multi-source datasets, including street-view imagery, GIS data, smartphone mobility data, and qualitative insights; applying and adapting state-of-the-art foundational AI and machine
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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other inside a tissue. In this project, you will build interpretable-by-design machine learning models for biological data that offer biological insights in a direct way. Such models will be applicable
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visit our webpages: About Quantum Circuits, Architecture, and Technology (QCAT) section About Quantum and Computer Engineering (QCE) department Job requirements You hold an MSc degree in Electrical
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modelling results to develop design principles for electrically driven processes; use the obtained insights to guide the design of electrochemical cleaning and separation technologies in close collaboration