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Field
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, biochemistry, cell/molecular biology, Honors (first class) or MSc degree in Chemistry/Pharmacology/Pharmaceutical Sciences Essential experience: Synthetic/medicinal chemistry (small molecule) andidates without
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, Master’s, and Doctoral degree programs) closely linked to both primary and applied research and high school teaching of the following sciences: Mathematics, Physics, Chemistry, Biology, and Earth sciences
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, microfluidics, colloidal synthesis, and mathematical modelling? Then you could be the ideal PhD candidate for this position. Self-assembled structures of colloidal particles and/or polymers at a liquid-air
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equivalent to a two-year master's degree. Your academic background needs to be relevant to the above-stated project objectives, e.g., civil engineering, mechanical engineering, physics, or applied mathematics
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of the study in peer-reviewed journals. Present papers at scientific conferences. Is Your profile described below? Are you our future colleague? Apply now! Education · A relevant MSc degree in e.g. engineering
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are looking for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in
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of software tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: APPLICANTS MUST COMPLY WITH THE MSCA MOBILITY RULES: in general, they must not have resided or carried out their main
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this role, we are looking for candidates to have the following skills and experience: Essential criteria MSc. in Neuroscience, Physics, Computer Science, or a related field Strong background in computational
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Participate in yearly retreats organized by the doctoral network participants Support the dissemination of software tools and concepts Supervise student projects and BSc/MSc theses Your Profile: Master’s degree
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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic