Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I sem. Oct 2, 2017 Jan 31, 2018
II sem. Mar 1, 2018 Jun 15, 2018
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2018 Feb 28, 2018
Sessione estiva d'esame Jun 18, 2018 Jul 31, 2018
Sessione autunnale d'esame Sep 3, 2018 Sep 28, 2018
Degree sessions
Session From To
Sessione di laurea estiva Jul 11, 2018 Jul 11, 2018
Sessione autunnale Nov 21, 2018 Nov 21, 2018
Sessione di laurea invernale Mar 13, 2019 Mar 13, 2019
Holidays
Period From To
Christmas break Dec 22, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Patron Saint Day May 21, 2018 May 21, 2018
VACANZE ESTIVE Aug 6, 2018 Aug 19, 2018

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrollment FAQs

Academic staff

A B C D E F G L M P R S T U V Z

Assfalg Michael

symbol email michael.assfalg@univr.it symbol phone-number +39 045 802 7949

Astegno Alessandra

symbol email alessandra.astegno@univr.it symbol phone-number 045802 7955

Ballottari Matteo

symbol email matteo.ballottari@univr.it symbol phone-number 045 802 7823

Bassi Roberto

symbol email roberto.bassi@univr.it symbol phone-number 045 8027916

Bellin Diana

symbol email diana.bellin@univr.it symbol phone-number 045 802 7090

Bettinelli Marco Giovanni

symbol email marco.bettinelli@univr.it symbol phone-number 045 802 7902

Bolzonella David

symbol email david.bolzonella@univr.it symbol phone-number 045 802 7965

Buffelli Mario Rosario

symbol email mario.buffelli@univr.it symbol phone-number +39 0458027268

Cecconi Daniela

symbol email daniela.cecconi@univr.it symbol phone-number +39 045 802 7056; Lab: +39 045 802 7087

Chignola Roberto

symbol email roberto.chignola@univr.it symbol phone-number 045 802 7953

Crimi Massimo

symbol email massimo.crimi@univr.it symbol phone-number 045 802 7924; Lab: 045 802 7050

Dall'Osto Luca

symbol email luca.dallosto@univr.it symbol phone-number +39 045 802 7806

Delledonne Massimo

symbol email massimo.delledonne@univr.it symbol phone-number 045 802 7962; Lab: 045 802 7058

Di Pierro Alessandra

symbol email alessandra.dipierro@univr.it symbol phone-number +39 045 802 7971

Dominici Paola

symbol email paola.dominici@univr.it symbol phone-number 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

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

Erle Giorgio

symbol email giorgio.erle@univr.it symbol phone-number +39 045802 8688

Frison Nicola

symbol email nicola.frison@univr.it symbol phone-number 045 802 7857

Furini Antonella

symbol email antonella.furini@univr.it symbol phone-number 045 802 7950; Lab: 045 802 7043

Gregorio Enrico

symbol email Enrico.Gregorio@univr.it symbol phone-number +39 045 802 7937

Lampis Silvia

symbol email silvia.lampis@univr.it symbol phone-number 045 802 7095

Molesini Barbara

symbol email barbara.molesini@univr.it symbol phone-number 045 802 7550

Pandolfini Tiziana

symbol email tiziana.pandolfini@univr.it symbol phone-number 045 802 7918

Perduca Massimiliano

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

Romeo Alessandro

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

Simonato Barbara

symbol email barbara.simonato@univr.it symbol phone-number +39 045 802 7832; Lab. 7960

Speghini Adolfo

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

Torriani Sandra

symbol email sandra.torriani@univr.it symbol phone-number 045 802 7921

Ugel Stefano

symbol email stefano.ugel@univr.it symbol phone-number 045-8126451
UgoliniSimone

Ugolini Simone

symbol email simone.ugolini@univr.it
Foto personale,  July 18, 2012

Vallini Giovanni

symbol email giovanni.vallini@univr.it symbol phone-number 045 802 7098; studio dottorandi: 045 802 7095

Vitulo Nicola

symbol email nicola.vitulo@univr.it symbol phone-number 0458027982

Zapparoli Giacomo

symbol email giacomo.zapparoli@univr.it symbol phone-number +390458027047

Zipeto Donato

symbol email donato.zipeto@univr.it symbol phone-number +39 045 802 7204

Zoccatelli Gianni

symbol email gianni.zoccatelli@univr.it symbol phone-number +39 045 802 7952

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
B
BIO/04
6
A
FIS/07
English language competence-complete b1 level
6
E
-

2° Year   activated in the A.Y. 2018/2019

ModulesCreditsTAFSSD
6
B
BIO/18

3° Year   activated in the A.Y. 2019/2020

ModulesCreditsTAFSSD
6
A
FIS/07
One course to be chosen among the following
One course to be chosen among the following
Training
9
F
-
Final exam
3
E
-
ModulesCreditsTAFSSD
12
B
BIO/04
6
A
FIS/07
English language competence-complete b1 level
6
E
-
activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
6
A
FIS/07
One course to be chosen among the following
One course to be chosen among the following
Training
9
F
-
Final exam
3
E
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S02690

Credits

12

Coordinator

Language

Italian

Scientific Disciplinary Sector (SSD)

MAT/05 - MATHEMATICAL ANALYSIS

The teaching is organized as follows:

Matematica

Credits

8

Period

I sem.

Academic staff

Simone Ugolini

Statistica

Credits

4

Period

I sem.

Academic staff

Roberto Chignola

Learning outcomes

------------------------
MM: Matematica
------------------------
This course aims at providing the students with the mathematical tools (set-theoretic and algebraic structures, differential and integral calculus in one or several real variables, ordinary differential equations) whose knowledge is indispensable for the achievement of the degree. A particular attention is paid to the concrete application of the learned notions. At the end of the course students should be able to use appropriately the mathematical language and the notions of the syllabus and furnish valid arguments in support of the solution of the proposed problems.
------------------------
MM: Statistica
------------------------
The aim of the course is to make the students acquainted with basic statistical ideas and methods and their applications in the correct planning of experiments, data sampling, analysis, and presentation. The course conjugates concepts of basic statistics and probability theory with real situations as they emerge in a standard biotechnology laboratory. The students acquire appropriate skills to understand how biological systems work and more generally to cope with real-life problems in different applied scientific fields. At the end of the course the students are able to: - analyse experimental observations and prepare professional reports - appropriately plan experiments - autonomously acquire new skills in specific fields of applied statistics

Program

------------------------
MM: Matematica
------------------------
1) Some notions of set theory.
2) The complete ordered field of the real numbers.
3) Euclidean distance and induced topology on the real line. Absolute value of a real number.
4) Cartesian plane.
5) Real functions of one real variable.
6) Polynomials and polynomial functions. Power, exponential and logarithmic functions. Trigonometric functions.
7) Limit of a function of one real variable.
8) Continuity of a function of one real variable at one point. Fundamental theorems on continuos functions.
9) Derivative of a function. Derivation rules. Fundamental theorems on differentiable functions.
10) Monotonicity of a function. Local and global minima and maxima of a function.
11) Convex functions.
12) Riemann integral. Integration rules. Improper integrals.
13) Ordinary differential equations.
14) Linear algebra. Matrices and operations on them. Determinant of a square matrix.
15) Distance between two points in the plane and geometrical loci. Conics.
16) Functions of more variables. Level curves and level sets.
17) Topology in R^2. Continuity of a function of 2 variables.
18) Differentiable functions of 2 variables. Partial derivatives.
19) Local and global minima and maxima of a function of more variables.
------------------------
MM: Statistica
------------------------
Each class introduces basic concepts of probability theory and applied statistics through combination of lectures and exercises. The exercises focus on the analysis of real experimental data collected in the teacher's lab or in other biotechnology labs. Lectures - brief introduction on the scientific method: the philosophical approach of Popper, Khun, and Lakatos and the concept of validation/falsification of hypotheses - variables and measurements, frequency distribution of data sampled from discrete and continuous variables, displaying data - elements of probability theory: definition, a brief history of probability, the different approaches to probability, the rules for adding and multiplying probabilities, Bayes' theorem - discrete probability distributions: the Binomial and the Poisson distributions and the limiting dilution assay with animal cells - continuous probability distributions: the concept of probability density, the Normal distribution and the Z statistics - statistical inference: the problem of deducing the properties of an underlying distribution by data analysis; populations vs. samples. The central limit theorem - the Student distribution and the t statistics. Confidence intervals for the mean. Comparing sample means of two related or independent samples - mathematical properties of the variance and error propagation theory - planning experiments and the power of a statistical test - the χ2 distribution and confidence intervals of the variance - goodness-of-fit test and χ2 test for contingency tables - problems of data dredging and the ANOVA test - correlation and linear regression The program follows the topics listed in the textbook up to chapter 17 (included) with the following extras: key aspects in probability theory, probability distributions in the biotechnology lab (practical examples), error propagation theory Reference textbook: Michael C. Whitlock, Dolph Schluter. Analisi Statistica dei dati biologici. Zanichelli, 2010. ISBN: 978-88-08-06297-0 Lecture slides are available at: http://profs.scienze.univr.it/~chignola/teaching.html

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Matematica Guerraggio, A. Matematica per le scienze con MyMathlab (Edizione 2) Pearson 2014 9788871929415
Statistica Michael C. Whitlock, Dolph Schluter Analisi Statistica dei dati biologici Zanichelli 2010 978-88-08-06297-0

Examination Methods

------------------------
MM: Matematica
------------------------
The final exam is written and must be completed in 3 hours. Neither midterm tests nor oral exams will take place. The exam paper consists of 6 exercises. The total of the marks of the exam paper is 32. Any topic dealt with during the lectures can be examined. Students are not allowed to use books, notes or electronic devices during the exam. The mark of any exercise will take into consideration not only the correctness of the results, but also the method adopted for the solution and the precise references to theoretical results (e.g. theorems) taught during the lectures. The pass mark for the exam of the Mathematics module is 18.
------------------------
MM: Statistica
------------------------
At the end of the course students are expected to master the basic concepts of probability theory and of validation/falsification of hypotheses, and to apply these concepts to the analysis of experimental data collected in a generic biotechnology laboratory. To pass the final written test, students are asked to solve 4 exercises within a maximum of 2 hours. The exercises concern the analysis of problems as they are found in a biotechnology laboratory. During the test, students are allowed to use learning resources such as books, lecture slides, handouts, but the use of personal computers or any other electronic device with an internet connection is not allowed. Eight points are assigned to the solution of each exercise and all points are then summed up. To pass their test students must reach a minimum score of 18 points. The final score of the whole course in Mathematics and Statistics is calculated as the weighted mean of the marks obtained by students in both tests by taking into account the number of credits assigned to each course as weights: final grade = (2/3) x1 + (1/3) x2 where x1 and x2 are the marks obtained by students in their tests of Mathematics and Statistics, respectively.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Type D and Type F activities

Modules not yet included

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.

Graduation

For schedules, administrative requirements and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

List of thesis proposals

theses proposals Research area
Studio delle proprietà di luminescenza di lantanidi in matrici proteiche Synthetic Chemistry and Materials: Materials synthesis, structure-properties relations, functional and advanced materials, molecular architecture, organic chemistry - Colloid chemistry
Multifunctional organic-inorganic hybrid nanomaterials for applications in Biotechnology and Green Chemistry Synthetic Chemistry and Materials: Materials synthesis, structure-properties relations, functional and advanced materials, molecular architecture, organic chemistry - New materials: oxides, alloys, composite, organic-inorganic hybrid, nanoparticles
Dinamiche della metilazione del DNA e loro contributo durante il processo di maturazione della bacca di vite. Various topics
Il problema della donazione degli organi Various topics
Risposte trascrittomiche a sollecitazioni ambientali in vite Various topics
Studio delle basi genomico-funzionali del processo di embriogenesi somatica in vite Various topics

Attendance modes and venues

As stated in the Didactic Regulations, there is no generalised obligation of attendance. Individual lecturers are, however, free to require a minimum number of hours of attendance for eligibilitỳ for the profit exam of the teaching they teach. In such cases, attendance of teaching activities is monitored in accordance with procedures communicated in advance to students.

Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.

The course's teaching activities take place in the Science and Engineering area, which is composed of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma cluster, and Villa Lebrecht and Villa Eugenia located in the San Floriano di Valpolicella cluster. 
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.


Career management


Student login and resources


Erasmus+ and other experiences abroad