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or equivalent Skills/Qualifications Valued/Preferred qualifications: Experience in software solution development Experience with machine learning models Experience in R&D&I projects (Research, Development and
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to adapt to multidisciplinary environments and a focus on professional growth and development. Desirable requirements Good knowledge of quantitative methods (econometric models, time series econometric and
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for automatic species identification, the use of various modelling approaches (such as generalised linear models or mixed models), spatial analysis of the movement of animal species tracked by GPS, analysis
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Maus* et al, Immunity, 2017). 3. Metabolic senescence of cells (Maus et al., Cell Metabolism, 2017) contribute to cancer. The lab works with mouse models, in vitro models, and with human specimen
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interdisciplinary training in theoretical language models, clinical approaches, AI methods (e.g., NLP), and neuroimaging, with opportunities to participate in network-wide events and international training activities
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data analysis is required, particularly in the handling and interpretation of data arising from physical experiments or computational models relevant to nanoscience. Teamwork; Critical thinking and
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vacuum, chemistry labs and scanning probe microscopies. Fluent in English, good writing and interpersonal skills. Molecular modelling software and programming knowledge for data acquisition and data
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on well-established model organisms, in our lab we investigate the mechanisms of adaptation in understudied bacterial species. The candidate will use experimental evolution to investigate how bacteria with
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high degree of ambition and motivation, and with good personal qualities to work in our Team. - Good level in English. About the Gnm3 group: Our research focuses on the design, synthesis, and
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, collaborative teamwork and independence. These key characteristics make EIPP a role model, which has inspired similar programmes at research institutions throughout Europe and the World. Find out more about the