{"id":656,"date":"2026-05-06T16:37:57","date_gmt":"2026-05-06T14:37:57","guid":{"rendered":"https:\/\/www.dm.unipi.it\/phd-hpsc\/?page_id=656"},"modified":"2026-05-06T16:44:25","modified_gmt":"2026-05-06T14:44:25","slug":"research-projects","status":"publish","type":"page","link":"https:\/\/www.dm.unipi.it\/phd-hpsc\/research-projects\/","title":{"rendered":"Research Projects"},"content":{"rendered":"\n<p>The following research projects are available within the Ph.D. Programme in High Performance Scientific Computing (a.y. 2026\/2027), each associated with a funded scholarship.<\/p>\n\n\n\n<div class=\"wp-block-pb-accordion-item c-accordion__item js-accordion-item no-js\" data-initially-open=\"false\" data-click-to-close=\"true\" data-auto-close=\"true\" data-scroll=\"false\" data-scroll-offset=\"0\"><h4 id=\"at-6561\" class=\"c-accordion__title js-accordion-controller\" role=\"button\"><strong>HPSS \u2013 Applications to FLASH Radiotherapy<\/strong><\/h4><div id=\"ac-6561\" class=\"c-accordion__content\">\n<p><strong>Number of positions:<\/strong> 2<br><strong>Supervisor:<\/strong> <a href=\"https:\/\/orcid.org\/0000-0002-3302-3765\">Giuseppe Felici<\/a><\/p>\n\n\n\n<p>Research topics include computational methods and models for FLASH radiotherapy, as well as radiobiological investigations of the FLASH effect.<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-pb-accordion-item c-accordion__item js-accordion-item no-js\" data-initially-open=\"false\" data-click-to-close=\"true\" data-auto-close=\"true\" data-scroll=\"false\" data-scroll-offset=\"0\"><h4 id=\"at-6562\" class=\"c-accordion__title js-accordion-controller\" role=\"button\"><strong>High-Performance Scientific Computing for Quantitative Large Deviations in Deep Learning<\/strong><\/h4><div id=\"ac-6562\" class=\"c-accordion__content\">\n<p><strong>Number of positions:<\/strong> 1<br><strong>Supervisor:<\/strong> <a href=\"https:\/\/www.dm.unipi.it\/en\/person-details\/?person_id=63cef8880570144d28d41ca2\">Dario Trevisan<\/a><\/p>\n\n\n\n<p>PhD project within the OTODDLE applied research line, focusing on initialization and training of deep neural networks, quantitative estimates, HPC-oriented algorithms, and large-scale simulations, in close interaction with the research group.<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-pb-accordion-item c-accordion__item js-accordion-item no-js\" data-initially-open=\"false\" data-click-to-close=\"true\" data-auto-close=\"true\" data-scroll=\"false\" data-scroll-offset=\"0\"><h4 id=\"at-6563\" class=\"c-accordion__title js-accordion-controller\" role=\"button\"><strong>Open Frameworks for Advanced Finite Element Analysis in Multiphysics and Multiscale Systems<\/strong><\/h4><div id=\"ac-6563\" class=\"c-accordion__content\">\n<p><strong>Number of positions:<\/strong> 1<br><strong>Supervisor:<\/strong> <a href=\"https:\/\/www.dm.unipi.it\/en\/person-details\/?person_id=653b52328f0af760bdc427e8\">Luca Heltai<\/a><\/p>\n\n\n\n<p>The project focuses on the development of open-source frameworks for advanced finite element analysis in multiphysics and multiscale problems, integrating mathematical models, efficient algorithms, and scalable implementations, with validation on realistic applications.<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-pb-accordion-item c-accordion__item js-accordion-item no-js\" data-initially-open=\"false\" data-click-to-close=\"true\" data-auto-close=\"true\" data-scroll=\"false\" data-scroll-offset=\"0\"><h4 id=\"at-6564\" class=\"c-accordion__title js-accordion-controller\" role=\"button\"><strong>HPC Codes for Advanced Electronic Devices and AI\/ML Integration<\/strong><\/h4><div id=\"ac-6564\" class=\"c-accordion__content\">\n<p><strong>Number of positions:<\/strong> 1<\/p>\n\n\n\n<p>The research activity focuses on the development, implementation, and use of high-performance computing (HPC) codes for the design, simulation, and analysis of electronic devices based on advanced and innovative materials. In particular, complex physical and mathematical models are addressed to describe charge transport phenomena, multiphysics couplings, and nonlinear behaviors typical of next-generation devices. The use of parallel computing architectures enables large-scale simulations with high accuracy and reduced computational time. To support these activities, artificial intelligence and machine learning techniques are integrated for parameter identification, model order reduction, design optimization, and analysis of simulation data, thereby improving both the efficiency and predictive capability of computational tools.<\/p>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>The following research projects are available within the Ph.D. Programme in High Performance Scientific Computing (a.y. 2026\/2027), each associated with&hellip;<\/p>\n<p><a class=\"btn btn-dark btn-sm unipi-read-more-link\" href=\"https:\/\/www.dm.unipi.it\/phd-hpsc\/research-projects\/\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":166,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-656","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - 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