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directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify commonalities and distinct aspects of engineering
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or quantitative data analysis is a plus. You are interested in developing and applying novel technologies and are willing to learn and work across disciplinary boundaries. You collaborate with
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function. Strong organizational and communication skills. Ability to work both independently and collaboratively. Motivation to learn new experimental approaches and progressively develop an independent
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independently while being part of a collaborative team Our offer 🎓Learning & Growth: Take advantage of seminars, trainings and language courses to expand your skills 📋Structured Onboarding: Benefit from a
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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of Twente, in close collaboration with the MESA+ Institute for Nanotechnology and clinical and international partners. Information and application You can apply for this position until 1 October 2026 by
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. To learn more about our work environment, colleagues, leaders, students and innovative educational environment, visit www.torontomu.ca , check out @TorontoMet (external link, opens in new window) and
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pharmacy. In close collaboration with partners from industry, healthcare, and society, we contribute to the urgent challenges of our time, such as energy, sustainability, digitization, and medical technology
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will include design, execution, and reporting of both qualitative and quantitative studies in collaboration with senior researchers. Who we are The Department of Management is part of Aarhus BSS , Aarhus
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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance