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We are now looking for a PhD student in Quantitative Logistics with a focus on efficient and sustainable supply chains. Join an exciting project where you’ll analyze and develop strategies
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of flotation process parameters based on experimental results. Work closely with a multidisciplinary team, including experts in mineral engineering, chemistry, and process optimization. Supervise MSc/PhD
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project reporting; ensure optimal use of resources and smooth day-to-day operations. Mentorship and Training: Guide PhD students, postdocs, and technicians in experimental methods and good laboratory
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at the Massachusetts Green High Performance Computing Center (MGHPCC). You will help with optimization of code and utilization of scheduler features to maximize throughput of jobs. In addition, you will work with
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. et al. (2024). Design of high-performance entangling logic in silicon quantum dot systems with Bayesian optimization. Scientific Reports 14, 10080. https://doi.org/10.1038/s41598-024-60478-9
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optimization. Together with a dedicated partner from bioinformatics you will first survey pairs of drug discovery application problems and corresponding quantum algorithms, before you focus on promising
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» Other Biological sciences » Biological engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Denmark Application Deadline 31 Jan 2026 - 23:59 (Europe/Copenhagen) Type
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equipment. You will join an international multidisciplinary team. You will apply simulation, multi-objective optimization, and data-driven analytics to evaluate and compare material intralogistics handling
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(Stanford University, USA). Qualifications PhD in process mineralogy, mineral processing, mining, chemical or geological engineering, or a PhD in a related field with mining/mineral processing experience
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and detection, coding theory, and optimization. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or