LAURA FALIVENE | ADVANCED TECHNOLOGIES AND SKILLS FOR SCIENTIFIC RESEARCH
LAURA FALIVENE ADVANCED TECHNOLOGIES AND SKILLS FOR SCIENTIFIC RESEARCH
cod. 8860400035
ADVANCED TECHNOLOGIES AND SKILLS FOR SCIENTIFIC RESEARCH
| 8860400035 | |
| DEPARTMENT OF CHEMISTRY AND BIOLOGY "ADOLFO ZAMBELLI" | |
| Corso di Dottorato (D.M.226/2021) | |
| CHEMICAL, BIOLOGICAL AND ENVIRONMENTAL SCIENCES | |
| 2024/2025 |
| OBBLIGATORIO | |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2024 | |
| SPRING SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | ||
|---|---|---|---|---|---|
| STESURA DI ELABORATI SCIENTIFICI IN LINGUA INGLESE | |||||
| CHIM/02 | 1 | 8 | LESSONS | ||
| INTRODUZIONE ALLE COMPETENZE TRASVERSALI. | |||||
| SECS-P/08 | 1 | 8 | LESSONS | ||
| BANCHE DATI STRUTTURALI | |||||
| CHIM/02 | 1 | 8 | LESSONS | ||
| INTRODUZIONE ALL'INTELLIGENZA ARTIFICIALE. | |||||
| CHIM/04 | 1 | 8 | LESSONS | ||
| Objectives | |
|---|---|
| THE TEACHING COURSE “TECHNOLOGIES AND ADVANCED SKILLS FOR SCIENTIFIC RESEARCH” WAS DESIGNED TO INTEGRATE ADVANCED DATA ANALYSIS SKILLS WITH THE NEEDS EXPRESSED BY THE CURRENT WORK ENVIRONMENT. THUS, THE FINAL GOAL IS THE DEVELOPMENT OF TRANSVERSAL SKILLS FOR THE DESIGN, DEVELOPMENT AND MANAGEMENT OF COMPETITIVE RESEARCH ACTIVITIES. KNOWLEDGE AND UNDERSTANDING PHD STUDENTS WILL LEARN THE THEORETICAL CONCEPTS AND WILL BE ABLE TO UNDERSTAND HOW THE ACQUIRED SKILLS ARE CRUCIAL FOR INDIVIDUAL AND GROUP SUCCESS. PRACTICAL ACTIVITIES WILL ENABLE THE STUDENTS TO TEST SIMULATED DATA ANALYSIS AND ADVANCED RESEARCH METHODOLOGIES FOR SCIENTIFIC RESEARCH. JUDGMENT ABILITY THE COURSE IS DESIGNED TO HELP THE STUDENTS TO DEVELOP THE ABILITY TO EVALUATE THE QUALITY OF DATA REPORTED IN THE SCIENTIFIC LITERATURE AND TO CRITICALLY THINK ON PROCEDURES IN COMPLEX SITUATIONS. STUDENTS, THROUGH GROUP DISCUSSIONS WILL HAVE THE OPPORTUNITY TO EXPRESS INFORMED OPINIONS AND SUPPORT THEIR CHOICES, THUS CONSOLIDATING THEIR JUDGMENT AUTONOMY. COMMUNICATION SKILLS THROUGH AN INTERACTIVE TEACHING APPROACH AND THE PROMOTION OF GROUP COLLABORATION, STUDENTS WILL DEVELOP EFFECTIVE COMMUNICATION SKILLS. PARTICULAR EMPHASIS WILL BE PLACED ON THE THEMES OF EFFECTIVE COMMUNICATION, ACTIVE LISTENING AND INTERCULTURAL SENSITIVITY, WHICH REPRESENT FUNDAMENTAL ELEMENTS IN A GLOBAL MARKET. LEARNING SKILLS THE COURSE AIMS TO ENHANCE STUDENTS' ABILITY TO LEARN CONTINUOUSLY, PROVIDING THEM WITH TECHNIQUES FOR EFFECTIVE SELF-DEVELOPMENT AND CONSTANT IMPROVEMENT OF THEIR SKILLS AND KNOWLEDGE. PHD STUDENTS WILL BE GUIDED TO REFLECT ON THEIR LEARNING PROCESSES AND TO IDENTIFY THE MOST APPROPRIATE STRATEGIES FOR THEIR PERSONAL AND PROFESSIONAL GROWTH. |
| Prerequisites | |
|---|---|
| BASIC KNOWLEDGE OF CHEMISTRY, PHYSICS AND COMPUTER SCIENCE |
| Contents | |
|---|---|
| THE TEACHING COURSE CONSISTS OF 4 MODULES, EACH MODULE CONSISTING OF 8 HOURS, DEDICATED TO: MODULE A: WRITING SCIENTIFIC PAPERS IN ENGLISH - UNIQUE INDICATORS OF AUTHORS AND PUBLICATIONS (1H) - SOFTWARE FOR THE GENERATION, MANAGEMENT AND ARCHIVING OF BIBLIOGRAPHIC REFERENCES (ENDNOTEWEB, MENDELEY, ZOTERO) (2H) - COLLABORATIVE WORK (GOOGLEDOCS AND OVERLEAF). (3H) - SOFTWARE DEDICATED TO WRITING EQUATIONS (LATEX AND AUTOLATEX). (1 H) MODULE B STRUCTURAL DATABASES - CRYSTALLOGRAPHIC DATA. CARTESIAN COORDINATES AND CRYSTALLOGRAPHIC COORDINATES. THE CIF AND PDB FORMAT (2H) - STRUCTURAL DATABASES. CAMBRIDGE STRUCTURAL DATABASE AND PROTEIN DATA BANK. USE OF CONQUEST SOFTWARE (2H) - USE OF PROGRAMS FOR THE THREE-DIMENSIONAL VISUALIZATION OF SMALL MOLECULES: MERCURY (2 H ) - USE OF PROGRAMS FOR THE THREE-DIMENSIONAL VISUALIZATION OF MACROMOLECULES: CHIMERAX, HERMES (2H). MODULE C INTRODUCTION TO TRANSVERSAL SKILLS AND RESEARCH MANAGEMENT - INTRODUCTION TO TRANSVERSAL SKILLS (1H) - INTERPERSONAL COMMUNICATION AND ASSERTIVENESS (1H) - EMPATHY AND AGREEMENT LANGUAGE (1H) - SITUATIONAL LEADERSHIP (1H) - RESEARCH MANAGEMENT (4H) MODULE D INTRODUCTION TO ARTIFICIAL INTELLIGENCE - PRINCIPLES OF ARTIFICIAL INTELLIGENCE: BASIC CONCEPTS (2H) - “SUPERVISED” MACHINE LEARNING: ANALYZING LARGE DATA SETS, IDENTIFYING PATTERNS, EXTRACTING INFORMATION, PREDICTIONS (2H) - “UNSUPERVISED” MACHINE LEARNING: PATTERN RECOGNITION, CLASSIFICATION, CLUSTERING (2H) - APPLICATIONS IN THE FIELD OF CHEMISTRY AND CATALYSIS: PREDICTION OF CHEMICAL REACTIONS, DESIGN OF NEW MOLECULES, IDENTIFICATION OF MATERIALS WITH SPECIFIC PROPERTIES (2H) |
| Teaching Methods | |
|---|---|
| HE LECTURES ARE SUPPORTED BY SLIDE PROJECTIONS AND MULTIMEDIA MATERIALS AVAILABLE VIA THE WEB THROUGH DATABASES (E.G. SCOPUS, SCI FINDER, WEB OF SCIENCE). STUDENTS WILL BE ENCOURAGED TO USE THEIR OWN LAPTOPS TO INSTALL THE NECESSARY SOFTWARE PACKAGES AND USE THEM. MODULE C ALSO USES METHODOLOGIES IN METAPHOR, ROLE PLAY, SIMULATIONS AND CIRCLE TIME. |
| Verification of learning | |
|---|---|
| THE ACHIEVEMENT OF THE TEACHING OBJECTIVES WILL BE VERIFIED THROUGH PROJECTS PRESENTATION BY THE STUDENTS (INDIVIDUALLY AND BY GROUPS) OF PROJECTS. IN THIS WAY THEY WILL BE ABLE TO SHOW THEIR ABILITY TO COMBINE AND APPLY THE LEARNED CONCEPTS AND TEST THEIR TRANSVERSAL SKILLS IN A PRACTICAL AND REALISTIC CONTEXT. |
BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2025-01-27]
