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related discipline. They should be responsible, self-motivated, attentive to detail, and a strong command of English. The candidate must possess a strong publication record that demonstrate their capacity
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that combines data from different molecular levels (transcripts, proteins, metabolites), aided by in silico target prediction, will enable us to uncover putative target of the compound, which will then be
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is expected to contribute to foundational research in dynamic modeling, stability analysis, and control of coupled data center–grid systems. Emphasis will be placed on developing new theoretical
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, and traceability in accordance with the GDPR and the EU AI Act. Integrate predictive virtual biopsy models in distributed environments. Lead pilot experiments and monitor the convergence of federated
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. Anticipating the new legislation, the INPROBED project has been granted, which aims to precisely identify and modify cis-regulatory elements and transcription factor genes that control key physiological pathways
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health. The postdoctoral associate will also participate in related projects on cardiometabolic disease, cardiovascular imaging, multimodal prediction, and implementation of imaging-derived biomarkers
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. The research combines computational protein design with synthetic biology to develop new molecular functions and mechanisms for controlling the formation, organization, and functional properties of living
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
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: dr hab. Natalia Szóstak Research topic Prediction of response to immunotherapy in melanoma using metabolic signatures of the gut mycobiome. I. Project description
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and