Study plan

FOUNDATIONS - 1 & 2 sem - Mandatory for all PhD students

• Methods for Research
  • Intellectual property management
  • Research ethics
  • Scientific writing, positioning and oral presentation / Academic writing for Engineering
  • Fund Raising and Project Writing and Management

• Scientific and computer science foundation of artificial intelligence

• Research Applied Methods
  • Design of Experiments (DOE)
  • Statistical learning for research
  • Applied Quantitative Methods
  • Critical reading and research design
  • Product and Process Sustainability
  • Simulation Methods and Tools

The second year includes thematic courses that PhD candidates may select according to their research pathway, choosing from the following options:

• Academic Entrepreneurship;
• Advanced course in Python for Machine Learning;
• Analysis and control of complex networks;
• From a literature review to a conceptual framework: developing research models and hypotheses;
• Methods and tools for circular design;
• Methods and tools for automated management of scientific data;
• Research methodologies for complex systems;
• Research topics in Manufacturing and Service Operations Management (M&SOM);
• Influence of new production technologies on material properties;
• Advanced computational methods for engineering.

PhD students will be able to participate in research seminars periodically organized across the different areas of interest and will regularly present the progress of their dissertation work in dedicated research seminars.

PhD students will also have the opportunity to attend Summer and Winter Schools on topics aligned with the PhD program.