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— an interdisciplinary field spanning information theory, stochastic thermodynamics, and quantum physics — and will explore several research directions: Thermodynamic computing: Developing physics-inspired models
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to an individual who meets the following requirements: received higher education in a relevant field (biotechnology, biology); is a participant of the Doctoral School during the scholarship period (03.11.2025
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combined with in-situ validation data, including reflectance measurements and ecological surveys. This dataset will form the foundation for accurate training and validation of image classification models
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in the project or within 7 years prior to January 1 of that year (for those holding more than one Ph.D., the reference date is that of the first degree). This period may be extended by documented long
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Requirements 1. MSc degree in Computer Science, Computational Chemistry, or a related field; 2. PhD student status required during the contract period; 3. Experience in cheminformatics modeling or deep learning
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this position will be responsible for conducting research in the area of verification, testing and exploration of artificial intelligence models, active participation in lab meetings, scientific seminars and
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models of flowering and vernalization. They may facilitate the establishment of untapped new plant protein sources for feed and food production. Principal Investigator: dr Sandra Rychel-Bielska DESCRIPTION
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models and is carried out in collaboration with Prof. Graham Ogg, the scientific partner from the University of Oxford. The funding for this exciting project was obtained within the FIRST TEAM programme of
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school or doctoral studies under the former law) in the same disciplines. Readiness to work with animal models (rats) Basic experience in molecular biology techniques is desirable Teamwork skills and
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) for the period of 24 months with the possibility of extending up to 48 months, and with the possibility of increasing the amount of the stipend after the mid-term evaluation (in accordance with