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AI models. Identifying relevant modalities to enhance prediction performance, with a focus on multi-spectral sensors, will be a key research area. Additionally, anomaly detection for modalities other
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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the adoption and scaling of regenerative entrepreneurship practices? Which approaches, tools, and practices best enable regenerative entrepreneurs to create lasting systemic impact? The position offers a unique
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equivalent to a two-year master's degree Extensive and demonstrable experience (through publications or thesis work) with multi-parametric flow cytometry Experience with isolation and culture of human
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small-scale processing sector. By joining this project, you will contribute to the development of AI-powered tools that predict non-compliance, improve food safety monitoring, and ultimately protect
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include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale You may apply prior
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. The project offers a unique opportunity to contribute to both foundational research and practical applications. Your primary tasks will be to: Develop methods for streaming process mining of large-scale event
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an extrusion machine that produces large-scale earth blocks Building a 3D printer that utilizes earth materials for construction purposes Developing numerical process models that simulate 3D earth printing
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official description of grading scale Two letters of recommendation from relevant and appropriate referees or the names and contact details of two Referees (as former Supervisors/PIs). You may apply prior
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student with a background in biological engineering, biotechnology or similar. You will work under the supervision of Assistant Professor Raphael Ferreira on large-scale genome engineering in human T cells