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Field
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: Essential criteria PhD qualified in relevant subject area * An excellent theoretical and practical knowledge of the human immune system Extensive experience of immunology-focused laboratory assays Extensive
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researchers, external labs, and industrial partners. Candidate Profile: Required qualifications : PhD in Mineral Processing, Mining Engineering, Georesources Engineering, or related field. Proven experience in
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partners, and monitoring budgets. Required Qualifications : PhD: A PhD in digital public health, urban health, data science applied to health or urban planning, smart urban systems, or a related field
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to the supervision of PhD students and research internships. Criteria of the candidate: PhD in the field of Cryptography, Computer security or any related field. Strong publication record in high impact conferences
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: The Postdoctoral researcher will be expected to: Publish in high impact journals in the field. Participate to the supervision of PhD students and research internships. Criteria of the candidate: PhD in the field
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Master level (Co-) Supervision of master and PhD theses is highly encouraged For further information, please contact Prof. Iris Behrmann: Your profile A PhD in Biology, Biochemistry, Biotechnology
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-quality academic articles and publish them in internationally recognised, reputable journals. You will mentor and co-supervise PhD students affiliated with the project. You will assist with project-related
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You will be hired as one of two team-leads of a consortium of several PhD students and master students working on the development of Covalent Organic Frameworks, photocatalytic semi-conductors for a
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the field of chemistry, chemical engineering, physics or physical engineering. The PhD degree must be accredited or accepted in Europe. Your PhD and publication list clearly show a strong expertise in
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research group/supervisor from the list available in CINBIO’s website, as well as envisioned secondments, their objectives, extent, and benefits for the candidate’s career; 3) a summarized data management