Formazione e ricerca

Attività Formative del Corso di Dottorato - 2024/2025

In questa pagina sono riportate le attività formative del corso di dottorato per l'anno accademico 2024/2025. Ulteriori attività verranno aggiunte durante l'anno. Ti invitiamo a verificare regolarmente la presenza di aggiornamenti!

Istruzioni per i docenti: gestione delle lezioni

Offerta formativa da definire

Attività Formative della Scuola di Dottorato - 2024/2025

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

1. PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, instructions will be sent well in advance. No confirmation e-mail will be sent after signing up. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS

Crediti: 2

Lingua di erogazione: English

Docente:  Luigina Mortari

DOTTORATO E MERCATO DEL LAVORO: WORKSHOP FORMATIVI PER DOTTORANDI E NEO-DOTTORI DI RICERCA

Crediti: 4

Lingua di erogazione: Italiano

ARE YOU SURE YOU CAN DEFEAT A CHATBOT?

Crediti: 1

Lingua di erogazione: Italiano

MEETING UKRAINE: THE IMPACT OF WAR AND FUTURE OPPORTUNITIES

Crediti: 1

Lingua di erogazione: Italiano

EMOTIONS, BELIEFS, AND SKILLS TO FACE CLIMATE CHANGE AND EMBRACE CLIMATE ACTION

Crediti: 0,5

Lingua di erogazione: Inglese

OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE

Crediti: 2

Lingua di erogazione: English

Docente:  Michele Scandola

COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING

Crediti: 4,5

Lingua di erogazione: English

Docente:  Matteo Bertucco

CSF DYNAMICS: ANATOMICAL AND FUNCTIONAL FEATURES

Crediti: 0,5

Lingua di erogazione: Inglese

Docente:  Alberto Feletti

DIFFERENTIAL DIAGNOSIS OF DEMYELINATING DISEASES OF THE CENTRAL NERVOUS SYSTEM

Crediti: 2

Lingua di erogazione: English

Docente:  Alberto Gajofatto

IL SONNO E I SUOI DISTURBI: FOCUS SULLE PARASONNIE E I DISTURBI DEL MOVIMENTO IN SONNO

Crediti: 1,5

Lingua di erogazione: italiano o inglese

Docente:  Elena Antelmi

IMAGING TECHNIQUES FOR BODY COMPOSITION ANALYSIS

Crediti: 1

Lingua di erogazione: Inglese/English

Docente:  Carlo Zancanaro

RESEARCH TECHNIQUES IN NEUROSCIENCE: MONITORING AND MODULATING NEURONAL ACTIVITY

Crediti: 2,3

Lingua di erogazione: non prevista

Docente:  Giuseppe Busetto

Crediti

5

Lingua di erogazione

English

Frequenza alle lezioni

Scelta Libera

Sede

VERONA

Obiettivi di apprendimento

Matlab is a numerical computing environment and high-level programming language. In the context of biomedical research, Matlab can be used to automate a wide variety of tasks, including record keeping, data analysis, and report generation.

Matlab favors scripting, i.e., writing in a text file a sequence of commands that can be executed reliably and consistently. Used properly, this method can be orders of magnitude more efficient and error-proof than interactive sessions with the most common computing platforms (e.g., Excel, SPSS, etc.) A well-tested script can be seamlessly run against any number of datasets and applied to similar experimental situations. Importantly, the scripts themselves represent accurate documentation of the performed analyses.

While a relatively steep learning curve is inevitable, especially in the absence of any computer programming background, Matlab can be mastered in small, incremental steps.

This mini course is intended as a general introduction to the concept of automated data analysis and report. The Matlab interface and the fundamentals of the scripting language will be presented first. A small set of common data analysis problems will then be tackled in the Matlab environment.

Please note that the available time is not sufficient to provide a detailed, in-depth knowledge of the language. My goal is to demystify the technology and provide insight into what can be accomplished and what the main hurdles are. Further training will be required to become fully proficient.

Bibliografia

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Modalità didattiche

Si richiede la frequenza di almeno 16 delle 20 ore previste.

Lezioni del Corso
Lezioni della Scuola di Dottorato

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Linee guida percorso formativo

Di seguito i file che contengono le Linee guida per il percorso formativo e il regolamento per l'acquisizione dei crediti formativi (CFU) per l'Anno Accademico 2023/2024.


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