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(PhD students, post-docs, researchers and teachers) and is located at the BMC-building (Biomedical Center). The expertise includes computational and experimental mechanics of biological tissues, where a
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with the project’s Principal Investigator, and practical implementation of this research with the AIMLeNS team. The role also offers ample opportunities to mentor PhD students, supervise MSc projects
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journals and at major conferences. The position will include supervision of PhD and MSc students, teaching and supporting in acquiring funds for future research projects from research funding agencies
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qualification deemed to be the equivalent of a PhD in molecular biology, biomedicine, or a related field is eligible for appointment as postdoctoral researcher. This eligibility requirement must be met no later
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degree (PhD), as required by the project Grant Agreement signed with the European Commission, at least one original publication in a peer-reviewed journal, a background in the relevant methods, a complete
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of appointment/assignment relevant to the subject area. The successful candidate should have a PhD in ecosystem ecology, biogeochemistry, physical geography, or a related field. Past experience of synoptic surveys
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taken into consideration. A suitable candidate will have a PhD in sociology, computer science, economics, statistics, political science or a corresponding subject of relevance to computational social
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evaluation process etc please visit: ambercofund.eu. Qualifications Minimum requirements are: Candidate needs to have a maximum 8 years after a doctoral degree (PhD), as required by the project Grant Agreement
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Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years
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Criteria Minimum Requirements for the Project: You must have no more than 8 years of work experience after earning your PhD, as required by the Horizon-Europe MSCA cofund project Grant Agreement. At least