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!

Instructions for teachers: lesson management

An introduction to NMR spectroscopy for the study of biomacromolecules

Credits: 1

Language: Inglese

Teacher:  Mariapina D'Onofrio

Application of multimodal imaging techniques in the study of the skeletal muscle

Credits: 0,5

Language: English

Teacher:  Barbara Cisterna

Chiral lanthanide-based materials for biological and technological applications

Credits: 1

Language: Italian

Teacher:  Fabio Piccinelli

Engineering photosynthesis to enhance productivity

Credits: 1

Language: Italian

Teacher:  Stefano Cazzaniga

Forensic diagnosis of alcohol intoxication and chronic alcohol abuse

Credits: 1

Language: Inglese/italiano

Teacher:  Federica Bortolotti

Forensic Genetics

Credits: 4

Language: Inglese

Teacher:  Stefania Turrina

Luminescent Nanomaterials for theranostics

Credits: 1

Language: Inglese.

Teacher:  Adolfo Speghini

Optical Imaging: principi e applicazioni

Credits: 1

Language: NA

Teacher:  Federico Boschi

Practical: protein structure determination by x-ray crystallography

Credits: 1,5

Language: Italian

Teacher:  Massimiliano Perduca

Valutazione del rischio da esposizione a nono materiali

Credits: 1

Language: English

Teacher:  Angela Carta

Surface Metrology with optical techniques

Credits: 1,5

Language: English

Teacher:  Claudia Daffara

Synthesis, characterization and applications of luminescent nanostructured materials

Credits: 1

Language: English

Teacher:  Francesco Enrichi

Tecniche di deposizione a film sottile per biomateriali, applicazioni biomediche e energia solare

Credits: 2

Language: English

Teacher:  Alessandro Romeo

Tracking nanoparticles in cells and tissues at transmission electron microscopy

Credits: 1

Language: English

Teacher:  Manuela Malatesta

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: as soon as we get new information, we will promptly publish it on this page.

Ambito per Dottorati

Ambito per i Corsi di Dottorato

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Other Free choice 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

Credits

5

Language

English

Class attendance

Free Choice

Location

VERONA

Learning objectives

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.

Bibliography

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.

Didactic methods

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

Faculty

A B C D E G M N P R S T Z

Ausania Francesco

symbol email francesco.ausania@univr.it symbol phone-number 0458127455

Bortolotti Federica

symbol email federica.bortolotti@univr.it symbol phone-number 045 8124618

Boschi Federico

symbol email federico.boschi@univr.it symbol phone-number +39 045 802 7272

Calderan Laura

symbol email laura.calderan@univr.it symbol phone-number 0458027562

Carta Angela

symbol email angela.carta@univr.it symbol phone-number +39 045 812 8270

Cazzaniga Stefano

symbol email stefano.cazzaniga@univr.it symbol phone-number +39 045 8027075

Cisterna Barbara

symbol email barbara.cisterna@univr.it symbol phone-number +39 045 802 7564

Daffara Claudia

symbol email claudia.daffara@univr.it symbol phone-number +39 045 802 7942

D'Onofrio Mariapina

symbol email mariapina.donofrio@univr.it symbol phone-number 045 802 7801

Enrichi Francesco

symbol email francesco.enrichi@univr.it symbol phone-number +390458027051

Gottardo Rossella

symbol email rossella.gottardo@univr.it symbol phone-number 045 8124247

Malatesta Manuela

symbol email manuela.malatesta@univr.it symbol phone-number +39 045 802 7569

Manfredi Riccardo

symbol email riccardo.manfredi@univr.it symbol phone-number +39 045 802 74 89

Munari Francesca

symbol email francesca.munari@univr.it symbol phone-number +39 045 802 7920

Nardon Chiara

symbol email chiara.nardon@univr.it

Perduca Massimiliano

symbol email massimiliano.perduca@univr.it symbol phone-number +39 045 8027984

Piacentini Giorgio

symbol email giorgio.piacentini@univr.it symbol phone-number +39 045 812 7120

Piccinelli Fabio

symbol email fabio.piccinelli@univr.it symbol phone-number +39 045 802 7097

Porru Stefano

symbol email stefano.porru@univr.it symbol phone-number 045 812 4294

Romeo Alessandro

symbol email alessandro.romeo@univr.it symbol phone-number +39 045 802 7936; Lab: +39 045 802 7808

Sbarbati Andrea

symbol email andrea.sbarbati@univr.it symbol phone-number +39 045 802 7266

Speghini Adolfo

symbol email adolfo.speghini@univr.it symbol phone-number +39 045 8027900

Turrina Stefania

symbol email stefania.turrina@univr.it symbol phone-number 045/8027622

Zancanaro Carlo

symbol email carlo.zancanaro@univr.it symbol phone-number 045 802 7157 (Medicina) - 8425115 (Scienze Motorie)
Course lessons
PhD Schools lessons

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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 2023/2024.

Documents

Title Info File
File pdf Dottorandi: linee guida generali (2023/2024) pdf, it, 111 KB, 26/02/24
File pdf PhD students: general guidelines (2023/2024) pdf, en, 127 KB, 26/02/24