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stakeholders, and FORM is a key founding player in CSlib’s steering and technical leadership . Who we are looking for We are looking for candidates who possess (or are nearing completion of) a PhD in Computer
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absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, or other forms of appointment/assignment relevant to the subject area
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, and public relations Your qualifications: At least a very good PhD in polymer research Completed university degree (M.Sc./M.Eng.) in polymer science or related field Professional experience and
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operation of the laboratory equipment and day to day running of the microwave pyrolysis laboratory Your profile The applicants should hold a PhD in applied chemistry, chemical engineering or similar. Both
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-impact peer-reviewed journals and contributing to project deliverables Engaging with academic, industry, and policy stakeholders to disseminate findings. We are looking for candidates who offer: A PhD in
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is available on a fixed term contract until 28 February 2029. If you are still awaiting your PhD to be awarded you will be appointed at Grade 6, spine point 30. Upon written confirmation that you have
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Supervision of PhD or MSc students Coordination with international partners Qualifications We seek a highly motivated postdoc candidate with a PhD degree and a background in chemistry, physics, nanoscience
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are leaders in such disciplines as genome-editing, AI/machine learning, protein engineering, cryo-EM/ET, NMR, single-molecule experiments and more. You will also collaborate with the wider community at St. Jude
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Two Postdoctoral Researchers in Cell Delivery-Based Beta Cell Replacement Therapy for Type 1 Diabete
applications, often taking on an interdisciplinary character. Cutting-edge contributions to areas such as computer systems, theoretical computer science, cybersecurity, computer vision, artificial intelligence
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms