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these to the project manager’s email address: [email protected] , with the subject line ‘Opus 29.3’): Cover letter CV Copies of obtained diplomas and certificates (if any) Copy or scan of candidate’s
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Warsaw University of Technology/Centre for Advanced Materials and Technologies, CEZAMAT | Poland | about 1 month ago
, CEZAMAT Research Field Physics Engineering » Electronic engineering Chemistry Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 23 Aug 2026 - 00:00 (Europe/Warsaw
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Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences (formerly Institute of Genetics and Animal Biotechnology PAS) | Poland | about 1 month ago
the following addresses: [email protected] (professor Irene Camerlink; PI’s email) and [email protected] (Message Subject: Application OPUS29 PhD - Name and Surname of the candidate) by August 27
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Institute of Technology The Łukasiewicz Research Network – Krakow Institute of Technology (https://kit.lukasiewicz.gov.pl/ ) is a member of the Łukasiewicz Research Network (https://lukasiewicz.gov.pl/en
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: 11.09.2026 IPG PAS WEBSITE: https://www.igr.poznan.pl/en/ PDS IPAS WEBSITE: https://psd-ipan.ichb.pl/ KEYWORDS: genetics, genomics, bioinformatics
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Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences (formerly Institute of Genetics and Animal Biotechnology PAS) | Poland | about 1 month ago
lymphomas, understand how its aberrant expression contributes to disease development, and develop effective strategies for targeting HDAC9 and monitoring its impact on BCL6 and p53. Project description: https
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chemistry Basic knowledge of molecular and cell biology techniques Prior experience with fluorescence, confocal, or electron microscopy and morphometric techniques is welcome Good computer skills and/or
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of the Doctoral School at the University of Maria Curie-Skłodowska. Before applying, candidates should first verify whether he/she fulfils the Doctoral School criteria. https://www.umcs.pl/en/formal-requirements
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a.m. to 3:30 p.m. Information about the competition: tel.: (32) 20-83-526, 20 83 570, e-mail: [email protected] Documents can also be sent electronically as a signed document using a trusted profile to
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries