Technological/Scientific Courses

Mandatory course

Research Methodology offered by IECS Doctoral School - DISI

Courses offered by IECS Doctoral School - DISI

Courses' description and scheduling: https://iecs.unitn.it/education/courses

• Advanced Multimodal Learning
• Advanced Techniques and Ethical Considerations in LLM Prompt Engineering
• AI Ethics Today
• AI/ML-Assisted Positioning and Sensing in Wireless Network
• Bridging Cooperative Games, Team Optimization, and Machine Learning: Basic Concepts and Case Studies
• Embodied and Conversational AI in Extended Reality
• Knowledge Graphs - advanced topics
• Mastering Foundation Models: Techniques and Applications for Advanced AI Tasks 
• Network intrusion detection with Deep Learning
• Radar and multispectral sensors in Earth observations and planetary exploration
• Research Methodology (Mandatory)
• Robot motion planning

Courses offered by Doctoral Programme in Materials, Mechatronics and Systems Engineering – DII

Courses' description and scheduling: https://www.unitn.it/drmmse/23/teaching-activities

Contact dii.phd@unitn.it to enrol on the courses listed below.

Materials Science and Engineering

• Biodesign applied to tissue engineering*
• Coatings for corrosion protection and electrochemical surface characterization
• Computational thermodynamics I
• Electron microscopy techniques – Theory
• Electron microscopy techniques – Practice
• Elemental analysis by X-ray spectroscopy – Practice*
• Environmental sustainability of the materials*
• Experimental mechanics of materials *
• Fracture nanomechanics
• Friction and Wear of Materials
• Materials science and technology
• Point defect chemistry, diffusion, and charge transport in ceramics
• Qualification SEM and TEM*
• Scanning probe microscopy – Theory and Practice*
• Thermal analysis
• X-ray diffraction: theory and applications to materials science and engineering

* Courses offered on demand (contact dii.phd@unitn.it)

Mechatronics and Mechanical Systems

• Factor Graphs for SLAM
• Legged robot control
• Modelling with Partial Differential Equations
• Optimization and Optimal Control for Epidemic Management and Public Health Interventions
• Robot learning from demonstration
• Saturated control systems

Electronic Systems and Integrated Microelectronic Systems

• Fundamentals of statistical estimation theory
• Laboratory of Electronic Instrumentation

Management Engineering

• Design and management of assembly lines in the era of Industry 5.0

Multidisciplinary Research Tools and Languages

• Multidisciplinary integrated design project

Courses offered by Doctoral Programme in Civil, Environmental and Mechanical Engineering – DICAM

Courses' description and scheduling: https://www.unitn.it/dricam/913/academic-year-2024-2025

Contact dicamphd@unitn.it to enrol on the courses listed below.

• An Introduction to Nonlinear Solid Mechanics
• Fundamentals of Environmental Sustainability
• Machine Learning & AI Methods - Theory, techniques, and Advanced
• Engineering Applications
• Applications of Perturbation Methods to Structural Dynamics
• GEOframe Winter School GWS2025
• Winterschool part I - Advanced numerical methods for free surface hydrodynamics
• Nonequilibrium and Metamaterials thermodynamic
• Collaborative approaches for the digital documentation, representation and design of territories and landscapes
• Stochastic Dynamical Modeling
• Design of linear and nonlinear metastructures 
• Reliability and randomized metamaterials 
• Winter School part II - Advanced numerical methods for hyperbolic equations
• Turbulence in environmental flows
• Environmental Sustainability - Advanced
• Snow Hydrology: Processes, Measurement, and Modeling
• Mathematical Methods for Engineering
• Hydro Climatology and Paleohydrology
• Environmental data management and analysis with GIS
• Instruments and methodologies for architectural design research
• X-ray Diffraction applied to the study of polycrystalline materials: theory and practice
• Models and Applications for Transportation Systems Analysis
• Life Cycle Assessment for the built environment: theory, methods, and applications
• Integrated river morphodynamics
• Applied Limnology: A Practical Introduction to Monitoring and modelling of lakes
• Numerical Modelling of Weather and Climate
• Advanced geomatics and Earth observation for environment
• Molecular Dynamics: a primer with elements of statistical mechanics
• Introduction to the mechanics of multiscale disarranged continua through structured deformations
• On water. Designing climate-responsive landscape and infrastructure
• Ground Penetrating Radar for Civil and Environmental Inspections
• Inverse Problems and Electromagnetic Diagnostics for Environment
• Surface Electromagnetics for Wireless Communications and Sensing
• Radar Systems and Technologies
• Phased Array Antenna Analysis and Synthesis
• Electromagnetic Field Theory and Applications
• Soundscape in the built environment: theory, methods, and application to the field of building ventilation

Courses offered by Doctoral Programme in Physics

Courses’ description and scheduling are available at: https://www.unitn.it/drphys/en/129/training-programme

• Advanced techniques in experimental physics
• Multiscale modeling: from the atom to the cell
• Data Analysis methods for Physics
• Advanced statistical mechanics: Relaxation to equilibrium and transport phenomena
• Electron-Atom Collisions and Spin-Polarization Phenomena
• Entanglement in Many-Body Systems: from Concepts to Algorithms
• Implementing robust and reproducible scientific workflows with Python and Git
• Optical and spectroscopic diagnostic of materials for photonics
• Quantum sensing
• Radiation Chemistry
• Space-based observation techniques and methods
• Physics of Magnetic Resonance Imaging
• Astrochemistry 
• Many-body physics with ultracold atoms and light
• Advanced topics in quantum many body physics: from strongly interacting to topological matter 
• Molecular Modeling, Design and Graphics
• Physical methods in polymer science 
• ECT* Doctoral Training Programme 
• Communication and dissemination in Physics

Courses offered by Doctoral Programme in Biomolecular Sciences - CIBIO

Courses’ description and scheduling are available at: https://www.unitn.it/drbs/36/teaching-activities

Contact phd.bioscie@unitn.it to enrol on the courses listed below.

• Laboratory safety course
• Introduction to data protection, security, and privacy
• Scientific Publishing & Communication
• The rules of research: introduction to biolaw and research integrity
• Science and Diplomacy: facing global challenges
• Decoding your science
• Introduction to the CIBIO Core Facilities
• Make scientific figures better and faster Module A: data visualization
• Make scientific figures better and faster Module B: images and figure composition

Biomolecular Curriculum

• RNA Molecular Biology and Biotechnology
• Chemical modifications and organic synthesis of biomolecules
• From FLIES, FISH and MICE, how to perform cutting-edge science to study human diseases.
• Advanced imaging approaches in Biomedicine
• Neural Stem cell
• Epigenetics mechanisms and their role during Cell Differentiation and transformation, Metabolism, Neuronal diseases
• Regenerative medicine and Artificial Intelligence applications to biomedicine
• Statistical methods for experiment design and data analysis

Bio - Industry Curriculum

• Entrepreneurial Basic Skills for Biotech Module 1: From innovation to a business model
• Entrepreneurial Basic Skills for Biotech Module 2: Working on a business plan
• Preclinical research and clinical development programs of drugs
• Inside Pharmas: Exploring R&D Organizations, Teams, Roles and Drug Portfolio
• Liquid biopsy: principles, technologies and diagnostic perspectives
• Understanding and modeling drug dose - response relationships for drug development
• From research to market of medical laboratory testing: readiness levels, optimal design of experiments, diagnostic tests development, quality and regulatory compliance

Quantitative Biology Curriculum

• Introduction to metagenomics
• Getting started with R and RStudio: a hands-on introduction
• Data Exploration
• Applied Statistics for High-Throughput Biology with Application to Single-cell Sequencing

Image by Gerd Altmann from Pixabay