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Field
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-oncological risk assessment Evaluation, analysis, and visualization of data Documentation of laboratory work Collaboration with project partners and regular presentation of results Your profile: M.Sc. or a
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samples Evaluation, analysis, and visualization of data Documentation of laboratory work Collaboration with project partners and regular presentation of results Your profile: M.Sc. or a degree in a natural
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research interest. You have a background in computer science, visual computing and computer vision or at least a strong interest. You have a background in nuclear technology, radiation physics and nuclear
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of investigation results for genuine system improvement. Supervisor: prof. Ing. Miroslav Žitňák, PhD. More information about PhD position: https://tf.uniag.sk/sk/doktorandske-studium-2 Additional admin information
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optimize production. Supervisor: doc. Ing. Martin Kotus, PhD. More information about PhD position: https://tf.uniag.sk/sk/doktorandske-studium-2 Additional admin information: renata.zahorska@uniag.sk Where
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manuscripts; 6. Presenting scientific data at international conferences. Website for additional job details https://matinf.uj.edu.pl/ Work Location(s) Number of offers available2Company/InstituteJagiellonian
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ASSOCIACAO ISCTE CONHECIMENTO E INOVACAO - CENTRO DE VALORIZACAO E TRANSFERENCIA DE TECNOLOGIAS | Portugal | 11 days ago
8 Apr 2026 Job Information Organisation/Company ASSOCIACAO ISCTE CONHECIMENTO E INOVACAO - CENTRO DE VALORIZACAO E TRANSFERENCIA DE TECNOLOGIAS Research Field Anthropology Criminology Sociology
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for the division is the Visualization Center C, a unique science center in Norrköping that engages the public through data-driven installations and 3D fulldome experiences. Read more at http
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. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ Background and description of tasks Our group develops new single-cell multiomic methods to characterize microbial
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would be happy to discuss PhD projects related to these aims, as there is some flexibility in research directions. Characterise behaviourally-relevant visual and semantic dimensions by the use of large