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Dr. Alan Crivellaro, University of Cambridge

This course is designed to help students, researchers and teachers to master effective scientific presentation skills. It will not impose a presentation style, but participants will have the opportunity to think about their presentation style and further develop it towards clarity and efficiency. Whether complete beginner or have some speaking experience, the course suits all needs. During the course, a very friendly environment will be built up, with supportive and non-judgmental space and time to practice speaking and learn from each other. After the course, participants will have a set of tools that will help them immediately improve their presentations and a framework for continuous improvement.

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Course shared with the MSc in Analysis and Management of the Environment. Basic course in environmental sensors and datalogger programming offered to our PhD students by University of Udine. For more information contact. The course will be held every Friday from 8:30 to 12:30 at University of Udine

Course offered by the PhD program. Aim of the course is to provide theoretical and practical knowledge about Remote sensing applications for environmental monitoring with particular reference to the use of satellite remote sensing imagery for deriving qualitative and quantitative information about the territory and its change in time. Information derived from LiDAR and SAR surveys will be also discussed. At the end of the course, the PhD student will be able to use advanced software tools (i.e. GEE) for the analysis and management of georeferenced databases in different applications of Environmental Sciences. Dr. Antonio Tomao

Course offered by the PhD program. The course will provide advanced information on the following topics: importance of water availability for plant productivity and distribution; terminology in plant and soil water relations; water potential and hydraulic conductance/conductivity; water status and availability in the critical zone; water uptake from root systems; long-distance water transport in the xylem; plant hydraulic efficiency vs safety; xylem embolism; leaf hydraulic architecture; stomatal movements and transpiration; climate change impacts on plant water relations. 

Course offered by the PhD program. The course content is designed to bridge the gap between basic R coding and basic/advanced statistical modelling. The course will consist of series of modules, designed to build required skills to perform a family of analyses that is frequently encountered in the biological and ecological literature. The following topics will be considered: 1 - Introduction to R: introduction of some fundamental statistical concepts and coding practices usign R and specific GUIs (Rcommander and Rstudio). Data manipulation & visualization using available packages such as ggplot2 and GrapheR; 2 – Classic Linear Models: Univariate regressions, diagnostics & plotting fits, Adding additional continuous predictors (multiple regression); quantile regression; scaling & collinearity; Adding factorial (categorical) predictors & incorporating interactions (ANCOVA); 3 – Advanced Linear Models: Generalised Linear Models (binomial and count data); Mixed effects models; Nonlinear models; Model selection & simplification (likelihood ratio tests, AIC, glmmulti); 4 – Geo-statistical linear models: An overview of model-based geostatistics; Classical parameter estimation; Empirical and Theoretical Semivariograms; geostatistical model estimation; kriging; 5 – Analysis of diversity patterns using the “vegan” package: classic alpha and beta-diversity indices (Shannon, Simpson, Pielou, Whittaker, Jacard); Rarefaction analysis, Distance Decay analysis.; 6- Analysis of multivariate datasets: Cluster analysis, PCA, RDA, PCOA, nMDS, variance partition techniques. 

For the complete list, please see at https://www2.units.it/dottorati/it/?file=Formazione.inc 

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