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Description Objectives: 1) Improve the biomanufacturing efficiency through a combination of advanced computational and experimental techniques (in model organisms such as P. pastoris and C. necator), along with
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Learning for Foundation Models’, where the aim is to adapt these models to new tasks without forgetting previous knowledge. The precise focus of the project can be defined in collaboration with
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data in order to identify the different cooling stages and analyse the influence that different parameters may have on heat treatment D. Detailed numerical modelling of the heat treatment process to be
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of multimedia datasets (voice, text, etc.). Development of predictive models for cognitive impairment and Parkinson's disease using signal processing and machine learning techniques. Development and debugging
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secondments: (i) Viva, Seville, Spain, mentor I. H. Rodriguez (4 months): Design of filtration systems and modules with energy-efficient models for conventional and catalytic membranes. (ii) Biosnar, Vaske
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(mammalian cell cultures) and whole tissue level (preclinical cancer models). Main Tasks and responsibilities: The PhD candidate researcher will focus primarily on laboratory-based experimental work in the
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it is not essential. The candidate must be fluent in English and Spanish. 4. Project Name & Code PID2024-162474NB-I00: Deciphering the role of rh37 in translation in response to aba and its regulation