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Field
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communities to environmental stresses and the cascading effects on ecosystem functioning. - Setting up experiments - Ecophysiological measurements in the laboratory - Statistical analysis of collected data
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- 4 Additional Information Eligibility criteria • PhD in cognitive neuroscience or neuroimaging. • Strong experience in acquisition and analysis of EEG and/or fMRI data. • Previous experience with
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for pursuing the analysis of data from a research project focused on the identification of clinical, genetic, and bacteriological factors involved in the development of severe bacterial infections (SBI) in
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FieldEnvironmental scienceYears of Research ExperienceNone Additional Information Eligibility criteria PhD Thesis in population ecology Skills in data analysis, GIS data and database management Skills in writing
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start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute from the onset. You will liaise with external collaborators and
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with PhD and master students and with medical doctors. You will start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute
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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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for recombinant protein expression. -Producing and purifying proteins from bacterial expression systems. -Participating in quantitative interactomics experiments and data analysis. Required qualifications -PhD
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, and ion transport is strongly desirable. ● Good command of scientific programming (e.g., Python, C/C++) and scripting for simulations and data analysis. ● Interest or experience in AI/ML tools applied
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collaboration, dedicated to the direct detection of dark matter. They will contribute to various activities including data taking, data analysis, and Monte Carlo simulations. The candidate will be involved in