Training and Research
PhD Programme Courses/classes - 2024/2025
This page shows the PhD course's training activities for the academic year 2024/2025. Further activities will be added during the year. Please check regularly for updates!
Inflectional Morphology (Winter School)
Credits: 2,5
Language: English
Teacher: Stefan Rabanus
Linguistics and Large Language Models
Credits: 2,5
Language: English
Teacher: Denis Delfitto, Andrea Padovan, Gaetano Fiorin, Andrea Padovan
Generation and Analysis of Corpora
Credits: 2,5
Language: Italian
Teacher: Andrea Abel
Investigating linguistic variables using oral data: the AlpiLinK corpus
Credits: 0,5
Language: English
Teacher: Stefan Rabanus
Theory and practice of transcription
Credits: 2,5
Language: Italian
Teacher: Lorenzo Spreafico
PhD school courses/classes - 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.
Teaching Activities ex DM 226/2021: Linguistic Activities
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Arts and Humanities]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Law and Economics]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Life and Health Sciences - 1 st Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC PRESENTATION SKILLS [Life and Health Sciences - 2 nd Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Arts and Humanities]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Law and Economics]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Life and Health Sciences - 1 st Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Life and Health Sciences - 2 nd Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Natural Sci. and Engineering-1st Session]
Credits: 2,5
Language: English
ENGLISH FOR ACADEMIC WRITING SKILLS [Natural Sci. and Engineering-2nd Session]
Credits: 2,5
Language: English
Teaching Activities ex DM 226/2021: Research management and Enhancement
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Arts and Humanities]
Credits: 2,5
Language: Italian
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Law and Economics]
Credits: 2,5
Language: Italian
SEMINARIO AVANZATO SULLE RISORSE BIBLIOTECARIE PER LA RICERCA [Scientific Area]
Credits: 2,5
Language: Italian
Teaching Activities ex DM 226/2021: Statistics and Computer Sciences
CORSO STATISTICA - LIVELLO BASE
Credits: 2,5
Language: English
INTRODUCTION TO PROBABILITY (MODULE I)
Credits: 1
Language: English
Introduction to Probability (module II)
Credits: 1
Language: English
Teacher: Marco Minozzo
Introduction to Statistical Inference
Credits: 1
Language: English
Teacher: Marco Minozzo
USO DI R PER L'ANALISI STATISTICA - LIVELLO BASE
Credits: 1
Language: English
Validità e affidabilità delle misure e dei test diagnostici
Credits: 0,5
Language: English
Teacher: Alessandro Marcon
APPLICATION OF META-ANALYSIS TO THE EPIDEMIOLOGICAL OR MEDICAL FIELD
Credits: 1
Language: English
Teacher: Giuseppe Verlato
CORSO STATISTICA - LIVELLO INTERMEDIO
Credits: 2,5
Language: English
DETERMINATION OF SAMPLE SIZE TO ACHIEVE A PREDEFINED PRECISION OR POWER
Credits: 0,5
Language: English
Teacher: Giuseppe Verlato
GENERALIZED LINEAR MODELS: LOGISTIC REGRESSION, LOGLINEAR MODEL, POISSON MODEL
Credits: 1
Language: English
Teacher: Lucia Cazzoletti
Disegno dello studio nella ricerca osservazionale e sperimentale
Credits: 1
Language: English
Teacher: Alessandro Marcon
Survival analysis: log-rank test, Kaplan-Meier survival curves, Cox regression model
Credits: 1,5
Language: English - Inglese
Teacher: Simone Accordini
USO DI R PER L'ANALISI STATISTICA - LIVELLO INTERMEDIO
Credits: 0,8
Language: English
Teacher: Alessandro Mantovani
Teaching Activities: Free choice
DOING INTERVIEWS IN QUALITATIVE RESEARCH
Credits: 2
Language: English
Teacher: Chiara Sità
PROGETTAZIONE E CONDUZIONE DI FOCUS GROUP
Credits: 2
Language: Italian
PROTECTING PSYCHOLOGICAL WELL-BEING IN THE PHD PROGRAM. DEVELOPMENT AND ENHANCEMENT OF PERSONAL STRATEGIES AND ATTITUDES PREDISPOSING TO PROFESSIONAL SATISFACTION AND ETHICAL COLLABORATION
Credits: 1
Language: Italian
Teacher: Michela Rimondini
QUANDO LA RICERCA SI FA ETICA (PERCORSO ORGANIZZATO E FINANZIATO DAL TEACHING AND LEARNING CENTER DI UNIVR)
Credits: 2
Language: English
Teacher: Roberta Silva
Workshop /Participatory approaches and methods in doing research with local actors
Credits: 1,5
Language: English
Teacher: Antonietta De Vita
...E SE VOLESSI FARE IMPRESA
Credits: 1
Language: Italian
IMPARA IL MARKETING DIGITALE
Credits: 1
Language: Italian
LA POESIA ITALIANA ALL'ESTERO
Credits: 1
Language: Italian
Teacher: Massimo Natale
THE EMPIRICAL PHENOMENOLOGICAL METHOD (EPM): THEORETICAL FOUNDATION AND EMPIRICAL APPLICATION IN EDUCATIONAL AND HEALTHCARE FIELDS
Credits: 2
Language: English
Teacher: Luigina Mortari
DOTTORATO E MERCATO DEL LAVORO: WORKSHOP FORMATIVI PER DOTTORANDI E NEO-DOTTORI DI RICERCA
Credits: 4
Language: Italian
ARE YOU SURE YOU CAN DEFEAT A CHATBOT?
Credits: 1
Language: Italian
MEETING UKRAINE: THE IMPACT OF WAR AND FUTURE OPPORTUNITIES
Credits: 1
Language: Italian
EMOTIONS, BELIEFS, AND SKILLS TO FACE CLIMATE CHANGE AND EMBRACE CLIMATE ACTION
Credits: 0,5
Language: English
OPEN SCIENCE: THE MIGHTY STICK AGAINST "BAD" SCIENCE
Credits: 2
Language: English
Teacher: Michele Scandola
COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING
Credits: 3,5
Language: English
Teacher: Matteo Bertucco
CSF DYNAMICS: ANATOMICAL AND FUNCTIONAL FEATURES
Credits: 0,5
Language: English
Teacher: Alberto Feletti
Differential diagnosis of demyelinating diseases of the central nervous system
Credits: 2
Language: English
Teacher: Alberto Gajofatto
sleep related disoders: focus on REM and NREM parasomnia and SR movement disorders
Credits: 1,5
Language: italiano o inglese
Teacher: Elena Antelmi
Tecniche di immagine per l'analisi della composizione corporea
Credits: 1
Language: Inglese/English
Teacher: Carlo Zancanaro
Tecniche di ricerca in neuroscienze: misurare e modulare l'attività neuronale
Credits: 2,3
Language: non prevista
Teacher: Giuseppe Busetto
COMPUTATIONAL MECHANISMS UNDERLYING SENSORIMOTOR LEARNING (2024/2025)
Teacher
Referent
Credits
3.5
Language
English
Class attendance
Free Choice
Location
VERONA
Learning objectives
Motor learning has traditionally focused on how predictive or feedforward control is updated by past errors and has generally assumed that adaptation is driven by a single process, that variability is undesirable, and that learning, and control are shaped by a trade-off between speed and accuracy. The course will review recent research that examined how learning shapes both predictive and reactive control mechanisms and has shown that adaptation involves multiple, interacting processes, that the motor system tunes variability to the learning task, and that accuracy is not necessarily gained at the expense of speed. Course contents: - Skills acquisition in sensorimotor learning - Variability in sensorimotor learning - Reward in sensorimotor learning - Bayesian processing in sensorimotor learning
Prerequisites and basic notions
Bases of muscle neurophysiology and motor control
Program
Motor learning has traditionally focused on how predictive or feedforward control is updated by past errors and has generally assumed that adaptation is driven by a single process, that variability is undesirable, and that learning, and control are shaped by a trade-off between speed and accuracy. The course will review recent research that examined how learning shapes both predictive and reactive control mechanisms and has shown that adaptation involves multiple, interacting processes, that the motor system tunes variability to the learning task, and that accuracy is not necessarily gained at the expense of speed.
Course contents:
- Skills acquisition in sensorimotor learning
- Variability in sensorimotor learning
- Reward in sensorimotor learning
- Bayesian processing in sensorimotor learning
Bibliography
Didactic methods
The teacher will use:
a) Lecture-style instruction
b) Group style activity through the discussion of scientific articles related to the topics covered during lectures.
Learning assessment procedures
The full attendance (100%) at the course will be required to obtain the CFU.
There will not be a final assessment for the course.
Assessment
The full attendance (100%) at the course will be required to obtain the CFU.
There will not be a final assessment for the course.
Criteria for the composition of the final grade
There will not be a final assessment for the course.
Faculty
daniele.artoni@univr.it
+39 045802 8465
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Guidelines for PhD students
Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2024/2025.
Documents
| Title | Info File |
|---|---|
39th-cycle PhD students: handout of first meeting (3 October 2023)
|
pdf, it, 115 KB, 26/09/24 |
|
Dottorandi: linee guida generali (2023/2024)
|
pdf, it, 118 KB, 12/12/23 |
|
PhD students: general guidelines (2023/2024)
|
pdf, it, 89 KB, 12/12/23 |
|
PhD students: guidelines for editing your personal webpage
|
pdf, it, 434 KB, 12/12/23 |
|
Second and third-year PhD students: general guidelines
|
pdf, it, 104 KB, 26/09/24 |
