The available 3-years positions in the 40th cycle 40 (starting for A.Y. 2024-2025 on November 1st, 2024) are updated on this web page on a daily basis.
This is needed to give visibility of the positions to all interested students who may want to apply, regardless the fact that - during this phase of constant updates of the official PhD card - some positions might not appear prmptly on the aforementioned official card.
Potentially interested students are hence strongly encouraged to review the positions on this web page, and - if interested - apply for the DSC selection process before the deadline.
(last update: 09 June 2024)
-- open scholarship -- (i.e. no specific pre-defined thematic area)
FUNDING ENTITY: partially funded by the central budget and co-financed by the Department of Computer Science and Engineering (DISI) and the Department of Electrical, Electronic, and Information Engineering "G. Marconi" (DEI)
CONTACTS: please refer to the PhD coordination/secretariat for general inquiries
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TITLE: Genomics and Bioinformatics, Medicina personalizzata e Computational Chemistry & Physics (scholarship 1/2)
FUNDING ENTITY: Italian Institute of Technology (IIT)
DESCRIPTION: The Italian Institute of Technology (IIT) conducts a wide range of advanced research in the fields of science and technology. The main areas of research include: Robotics, Nanotechnology, Neuroscience, Material Science, Health Technologies, Artificial Intelligence and Machine Learning, and Energy and Environment. In particular, in the field of neuroscience, IIT conducts research aimed at exploring the functioning of the human brain and nervous systems, seeking to understand the mechanisms underlying brain functions and neurological disorders, with potential applications in the diagnosis and treatment of neurodegenerative diseases. In Health Technologies, IIT conducts research on technological solutions to improve human health and well-being, including the development of medical devices, rehabilitation technologies, and advanced diagnostic tools. In Artificial Intelligence and Machine Learning, IIT works on developing algorithms and AI systems for a wide range of applications, including robotics, data analysis, and model prediction.
CONTACTS: please refer to the PhD coordination/secretariat
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TITLE: Genomics and Bioinformatics, Medicina personalizzata e Computational Chemistry & Physics (scholarship 2/2)
FUNDING ENTITY: Italian Institute of Technology (IIT)
DESCRIPTION: The Italian Institute of Technology (IIT) conducts a wide range of advanced research in the fields of science and technology. The main areas of research include: Robotics, Nanotechnology, Neuroscience, Material Science, Health Technologies, Artificial Intelligence and Machine Learning, and Energy and Environment. In particular, in the field of neuroscience, IIT conducts research aimed at exploring the functioning of the human brain and nervous systems, seeking to understand the mechanisms underlying brain functions and neurological disorders, with potential applications in the diagnosis and treatment of neurodegenerative diseases. In Health Technologies, IIT conducts research on technological solutions to improve human health and well-being, including the development of medical devices, rehabilitation technologies, and advanced diagnostic tools. In Artificial Intelligence and Machine Learning, IIT works on developing algorithms and AI systems for a wide range of applications, including robotics, data analysis, and model prediction.
CONTACTS: please refer to the PhD coordination/secretariat
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TITLE: Computational Physics (scholarship 1/2)
FUNDING ENTITY: National Institute for Nuclear Physics (INFN)
DESCRIPTION: The National Institute for Nuclear Physics (INFN) conducts advanced research in the fields of nuclear physics, subnuclear physics, and elementary particles. The main areas of research include: 1) Particle Physics: study of elementary particles, their interactions, and the fundamental forces governing the universe, for example, at large particle accelerators like the Large Hadron Collider (LHC) at CERN in Geneva. 2) Nuclear Physics: exploration of the structure and properties of atomic nuclei, understanding the interactions between protons and neutrons, and nuclear reactions. These studies have applications ranging from nuclear energy production to medicine. 3) Astrophysics and Cosmology: investigation of astrophysical and cosmological phenomena, such as gravitational waves, cosmic rays, dark matter, and dark energy, to understand the structure and evolution of the universe. 4) Theoretical Physics: development of models and theories describing the fundamental laws of nature, with a particular focus on quantum field theory, general relativity, and unification theories. 5) Technologies and Applications: development of advanced technologies, tools, and methodologies for scientific research. Innovations resulting from INFN research find applications in various sectors, including medicine, biology, computing, and security.
This scholarship aims to support doctoral research on advanced computing applications in INFN's scientific activities, and/or the development of foundational and innovative methods in data science and computation to support INFN's research mission.
CONTACTS: please refer to the PhD coordination/secretariat
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TITLE: Computational Physics (scholarship 2/2)
FUNDING ENTITY: National Institute for Nuclear Physics (INFN)
DESCRIPTION: The National Institute for Nuclear Physics (INFN) conducts advanced research in the fields of nuclear physics, subnuclear physics, and elementary particles. The main areas of research include: 1) Particle Physics: study of elementary particles, their interactions, and the fundamental forces governing the universe, for example, at large particle accelerators like the Large Hadron Collider (LHC) at CERN in Geneva. 2) Nuclear Physics: exploration of the structure and properties of atomic nuclei, understanding the interactions between protons and neutrons, and nuclear reactions. These studies have applications ranging from nuclear energy production to medicine. 3) Astrophysics and Cosmology: investigation of astrophysical and cosmological phenomena, such as gravitational waves, cosmic rays, dark matter, and dark energy, to understand the structure and evolution of the universe. 4) Theoretical Physics: development of models and theories describing the fundamental laws of nature, with a particular focus on quantum field theory, general relativity, and unification theories. 5) Technologies and Applications: development of advanced technologies, tools, and methodologies for scientific research. Innovations resulting from INFN research find applications in various sectors, including medicine, biology, computing, and security.
This scholarship aims to support doctoral research on advanced computing applications in INFN's scientific activities, and/or the development of foundational and innovative methods in data science and computation to support INFN's research mission.
CONTACTS: please refer to the PhD coordination/secretariat
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TITLE: Application of Data Science and Artificial Intelligence Techniques for the Multiparametric Analysis of Seismological, Geodetic, and Geophysical Time Series
FUNDING ENTITY: National Institute for Geophysics and Vulcanology (INGV)
RESEARCH TOPIC: In the last decade, the field of seismology has witnessed the generation of vast amounts and varieties of data, while the power of high-performance computing is rapidly growing. This data explosion has sparked growing interest in the seismological scientific community for the world of "data science," paving the way for the development of advanced computational skills to manage and organize "big data." At the same time, "data mining" and "machine learning" techniques are becoming increasingly crucial for a full understanding of seismic phenomena. The implications of this research could not be more significant, especially considering the crucial role seismology plays in earthquake prediction and prevention. This constitutes a powerful incentive to invest financial and human resources in this field. The proposed research project focuses on the application of data mining and machine learning methodologies for the multiparametric analysis of geophysical data, such as the variation of the Gutenberg-Richter b-value, the background rate, crustal geophysical parameters, source parameters such as stress drop, and deformations, in the preparatory phases before major earthquakes and during seismic sequences. The goal is to develop new data processing approaches that allow the extraction of valuable information from the joint analysis of different and heterogeneous datasets and to identify possible transients common to the various time series, useful for understanding the preparatory phase of earthquakes.
CONTACTS: Anna Maria Lombardi (annamaria.lombardiATingv.it), Licia Faenza (licia.faenzaATingv.it)
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