Scientifica Venture Capital has created Thesis
to spread the importance of investing in knowledge.
WHO IS IT AIMED AT?
Bachelor’s and Master’s graduates and undergraduates, enrolled in Italian Universities in scientific, technological, engineering and mathematical fields of study.
Thesis written in either Italian or English are accepted.
AWARD
Up to a maximum of 9 theses will be selected per academic year.
Selected candidates will receive a grant of € 3.000 and get access to a mentorship program on Entrepreneurship and the world of Startups.
PARTICIPATION GUIDELINES
The grants are awarded through a selection process that takes place three times per year.
Only Thesis defended within the 6 months prior to the application date are eligible for submission. The interested parties can apply by completing the form below.
Discover the winners
Author:
Thesis Title:
Faculty:
University:
Beatrice Annunziata Milano
Lesion Network Mapping of functional disability
Medicina e Chirurgia
Università di Pisa
Author:
Thesis Title:
Faculty:
University:
Giorgio Carbone
Deep Models of the Human Cortex to Predict fMRI Responses to Visual Scenes
Data Science
Università degli Studi di Milano – Bicocca
Author:
Thesis Title:
Faculty:
University:
Noemi Sgambelluri
Fostering Confidence: Evaluating Inter-Site Reproducibility of Bingham-NODDI Model Measures using Phantoms and In-Vivo Acquisitions
Fisica
Università di Bologna Alma Mater Studiorum
Author:
Thesis Title:
Faculty:
University:
Angelo Mulas
Comparison of octaweb configuration and annular aerospike nozzle for reusable launch vehicles
Aerospace Engineering
Politecnico di Torino
Author:
Thesis Title:
Faculty:
University:
Ilaria Rosa
Synthesis and characterization of nanoporous materials for gas storage
Scienze dei Materiali
Università degli Studi di Milano – Bicocca
Author:
Thesis Title:
Faculty:
University:
Ginevra Fulco
Studio degli Effetti della Radioattività Ambientale sui Quantum Bit Superconduttori
Fisica
Università degli studi di Roma La Sapienza
Author:
Thesis Title:
Faculty:
University:
Daniele Cucurachi
Quantum-Enhanced Monte Carlo Markov Chain Optimization
Fisica
EPFL – École Polytechnique Fédérale de Lausanne
Author:
Thesis Title:
Faculty:
University:
Matteo Scuderi
Inseguimento di traiettorie ed evitamento di ostacoli tramite Control Barrier Functions: implementazione via quadratic programming
Ingegneria Informatica e Automatica
Università degli studi di Roma La Sapienza
