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dissemination, and translational opportunities Job Requirements: PhD in Chemistry with a focus on computational/peptide/organic/machine learning or a closely related discipline At least one first-author
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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 18 hours ago
://drive.google.com/file/d/17SY2HfckkPZp8GVtRelkIxrGhikP92nN/view?usp=sharing Job Requirements REQUIRED: PhD in materials science, physics, electrical engineering, chemical engineering, or a related field by the start
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environment in Production Technology. With about 70 researchers, research engineers, and PhD students, it carries out research on welding, metal additive manufacturing (AM), and thermal spray manufacturing
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tracking for bioaerosol Applications are invited for a PhD position in the Air Quality and Particle Technology group (Prof. Dr. J. Wang). The successful candidate will be hosted by the Institute
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Engineering, Mechatronics, or Robotics, with a heavy emphasis on dynamic system theory, or a closely related discipline. Strong academic background in applied intelligent control techniques, machine learning
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17 Mar 2026 Job Information Organisation/Company cnrs Department lem3 Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Jun
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engineering Engineering » Mechanical engineering Mathematics » Applied mathematics Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 13 Apr 2026 - 23
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learning with no more than five years post receipt of this degree, in Electrical/Electronics Engineering, telecommunications, or related field. Other requirements include: Proven track record of publications
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, SIAM Review, 60(3):550–591 (2018). [4] Diederik P Kingma and Max Welling, Auto-Encoding Variational Bayes, International Conference on Learning Representations (ICLR) 2014 ArXiv. http://arxiv.org/abs