Research Methods in Science and Technology
PhD

The PhD program is designed to provide students with knowledge, competences, and skills needed to undertake research in science and technology with awareness, responsibility and method. To this purpose, the degree program provides the opportunity to: deepen ethical and methodological issues, develop critical sense, apply both qualitative and quantitative research methodologies, experience the development, characterization, validation and usage of formal and computational models, improve scientific and technical writing skills, and confront the international scientific community.

The first year will be dedicated to courses, exams and other teaching and research activities in Urbino, in the context of the Renaissance city, included in the UNESCO World Heritage.

Courses with exams will be taught in English, and will be structured into teaching modules of 4 ECTS each, corresponding to 8 hour of lectures + project work and study. Exams (written tests and/or papers and/or oral examinations) will be taken right after each course. An additional session of exams will be offered in September. Admission to the second year will depend on students’ achievement of a satisfactory score at final exams in each teaching module.

Seminars (with no exams) will address specific topics to provide additional opportunities of either deepening their main fields of interest or widening their research horizons.

Research projects are assigned at the beginning of the second year, which is mainly devoted to research.

PhD thesis will be completed during the third year, submitted and defended at the end of the last Academic Year.

Candidates are expected to spend a semester abroad.

First year

In the first year students are expected to take 15 short courses of 4 ECTS (8 hours), with final evaluation.  

• 8 mandatory courses on methodological aspects, ethics, technical writing, and transversal skills
• 5 area-specific courses
• 2 elective interdisciplinary course chosen either among those offered in different areas of the same program, or among those offered by other PhD programs of the University of Urbino

Second year

Mainly devoted to research

• Definition of the Research Project Proposal 
• Supervised research activity
• Participation to selected Doctoral courses, Seminars or Summer Schools
• Possible research experience abroad 

Students are expected to present the results of their work at International workshops and conferences and to submit papers for publication in international journals. 

Third year

Mainly devoted to thesis preparation and publications

• Thesis development and completion
• Participation to selected Doctoral courses and Seminars
• Possible research experience abroad 

Students are expected to present the results of their work at International workshops and conferences and to submit papers for publication in international journals.

COMMON MANDATORY COURSES 

• Ecological Models (Antonella Penna) LS8
  Introduction to the ecological functioning of ecosystems through the basic models and functions of population growth (exponential and logistic models), inter-specific relationships (competition, predation, foraging)  within community,  community structure and dynamic.
• Statistics in Experimental Research (Francesco Piergiovanni) PE1
  The course addresses the basic aspects of the statistical treatment of experimental data, from the correct analysis of the errors associated to each measurement, to the tests used for the determination of the statistical significance of an experimental result.
• Data Analysis (Matteo Montani) PE9
  Introduction to the use of Python in the exploratory analysis and display of data, with specific application to time-series analysis and multi-dimensional data. 
• Algorithmic Thinking and Computational Complexity (Valerio Freschi) PE6
  The aim of the course is to provide the methodological instruments required to understand, and possibly develop, efficient algorithmic solutions to real-world computational problems
• Optimization Methods (Raffaella Servadei) PE1
  The course aims to introduce classical optimization techniques, with particular attention to the applications.
• Critical Thinking (Gino Tarozzi, Pierluigi Graziani) SH4
  Fallacies, cognitive biases, slow and fast thinking, natural deduction, formal semantics.
• Scientific Method: Foundations and Problems (Vincenzo Fano) SH4
  Induction, Bayesianism, eliminativism, hypothetical-deductive method, bootstrapping.
• Scientific Communication Strategies (Pierangela Palma)
  Effective ways to communicate scientific information and disseminate scientific results

CHEMISTRY

• Drug Discovery and Development (Andrea Duranti) PE5
  The course aims to introduce the key principles and methods for drug discovery and development
• Molecular Structure Determination (Simone Lucarini) PE5
  The course provides a practice-oriented and systematic introduction to molecular structure determination by the most significant spectroscopic methods.
• Multicomponent Reactions in Organic Synthesis (Fabio Mantellini) PE5
  An introduction to multicomponent reactions in organic synthesis
• Advances in Solid Phase Microextraction (Janusz Pawliszyn) LS7
  The course presents the state of the art in Solid Phase Microextraction
• Sampling techniques for the analysis of organic molecules (Giorgio Famiglini) PE4
  The course aims to present the main sampling, purification and pre-concentration techniques of organic analytes in various matrices before instrumental analysis. 

EARTH SCIENCES

• Earth's Climate and the Carbon Cycle (Appy Sluijs) PE10
  This short course provides an overview of the interconnectedness of Earth's climate system components, focusing on the Carbon Cycle.
• Geology and research methods in geothermal energy: from electricity production to borehole heat exchangers (Alberto Renzulli) PE10
  The short course will provide an introduction on the geodynamic and geological constraints concerning the various possibilities to yield geothermal energy, then an overview of the research methods for this kind of renewable. It is going to deal with some examples of geological areas throughout the world currently exploited for both medium-high enthalpy geothermal energy and simple plants based on ground coupled heat pumps.
• Time series analysis of geological data (Luca Lanci) PE10
  The course is focused on time series analysis of geological data and proxy for paleo-climatic data. Parametric and non-parametric spectral methods will be introduced to recognise trends, periodic forcing and background noise. The approach of the course is practical and will make use of the R data analysis software.
• Analytical methods for rock-forming minerals (Michele Mattioli) PE10
  This course will give an introduction to the main mineralogical and petrographic methods (e.g., optical microscopy, SEM-EDS, diffraction methods, XRF, EPMA, ICP-MS, FTIR, AFM, Raman, TEM) which can be used in the characterization of Earth and material sciences, with particular focus on the advanced material technology.
• Geological data acquisition methods (Marco Menichetti) PE10
  This course will explore the advanced digital methods technologies (photogrammetric, TLS, Lidar etc) and tools of geoscience used in field an lab data acquisition. A combination of lectures and real examples of data collection and processing will be used to construct 3D models as a valuable research and education tool in all geosciences disciplines.

FORMAL MODELS, DATA ANALYSIS AND SCIENTIFIC COMPUTING

• Introduction to quantum computing (Catia Grimani) PE2
  Principles and perspectives of quantum computing: an overview of basic concepts and possible applications, with an introduction to quantum physics.
• Seeking Gravitational Waves (Gianpietro Cagnoli) PE9
  The course will give an introduction to General Relativity and astrophysical phenomena connected to the theory. It will then focus on gravitational waves detection by means of interferometric experiments.
• Partial differential equations: from modelling to theory (Giovanni Molica Bisci, Raffaella Servadei) PE1
  The main purpose of this course is to focus on the interplay between theory and modelling in problems arising in the applied sciences.
• Foundations of physics (Fred Muller) SH4
  Entanglement, realty of space-time, cosmological principle and statistical representation.
• Theory of Computation (Cuno Lorenz Klopfenstein, Valerio Freschi) PE6
  The course introduces the theory of computability starting from models and formalisms like Turing machine and recursive functions and presents the foundation of complexity theory.

The natural occupational outcome of the program is R&D in academic institutions, research centers, public administrations and companies. The level of expertise, awareness, maturity and experience acquired during the program allows PhDs to undertake careers entailing coordination and decision making skills and responsibility.