Details about funded positions - 38th Cycle - Curriculum 3

(3A) Sensors and techniques for the exploration of the Solar System

Funding institution: Istituto Nazionale di Astrofisica - INAF
Doctoral site: One of INAF site in Italy
Contact: Francesca Esposito (francesca.esposito [at] inaf.it) and Fabrizio Fiore (fabrizio.fiore [at] inaf.it)

The range of possible fields of scientific research connected to this theme is very broad and can range from the development of innovative sensors for space missions dedicated to the exploration of the Solar System, to the planning and design of new missions, to the laboratory study of planetary analogues, to the simulation of environments and processes active in the Solar System, to the study of the characteristics of the bodies of the Solar System starting from the analysis of the data acquired by the various space missions, to the development of theoretical models that describe processes and phenomena active in the Solar System.

The candidate, in agreement with the supervisor, will be able to choose the scientific theme most akin to his/her interests and training. He/she will then be able to carry out his/her research activity at one of the INAF sites where there are research groups interested or active in the identified scientific field.

(3B) Mathematical challenges in space science: theoretical and computational methods in Celestial Mechanics and Astrodynamics

Funding institution: Istituto Nazionale di Alta Matematica - INDAM
Doctoral site: Padova, Pisa, Roma Tor Vergata o Torino
Contact: Giovanni Federico Gronchi (giovanni.federico.gronchi [at] unipi.it)

This grant is devoted to the study of mathematical problems arising in the field of the dynamics of celestial bodies, taking also into account their applications to astronomy and space navigation, e.g. orbit determination, the N-body problem, low-thrust orbits in space missions. The techniques employed to deal with these problems can belong to different branches of mathematics, e.g. general theory of dynamical systems, perturbation theory, calculus of variations, computational algebra, numerical analysis.

(3C) Natural and synthetic analogues of the planet Mercury: mineralogical and petrological aspects

Funding institution: University of Florence
Doctoral site: Florence
Contact: Giovanni Pratesi (g.pratesi [at] unifi.it)

The Bepi-Colombo space mission is aimed at observing the planet Mercury and its surrounding environment. In particular, the study of Mercury is crucial for defining and validating models of planet formation and evolution, as well as for understanding the boundary conditions favorable for the emergence of life on our and other planets. Among the major scientific objectives of the mission, of particular interest to this Ph.D., is the study of the origin and evolution of a planet orbiting close to its star, more specifically the differentiation of a rocky planet as can be derived by the study of its surface composition and internal structure.

Within the Ph.D., the candidate shall define the possible mineralogy and petrology of Mercury based on compositional and spectroscopic data, acquired by the MESSENGER mission and relative to the surface of the planet. The candidate will then proceed to define the potential terrestrial and extraterrestrial analogs of the surface of Mercury, to the synthesis of analogous products, and to their complete mineralogical, petrological, and geochemical characterization. In addition, the candidate will perform a spectroscopic characterization of the analogs in the VNIR and MidIR ranges in support of the measurements performed by the VIHI and MERTIS instruments onboard BepiColombo.

(3D) Search, characterization and exploration of exoplanets and exoplanetary systems

Funding institution: University of Padua
Doctoral site: Padua
Contact: Giampaolo Piotto (giampaolo.piotto [at] unipd.it)

After 27 years since the discovery of the first exoplanet, more than 5100 planets in about 3800 exoplanetary systems have been discovered. A large amount of exoplanet search and characterization projects have been developed in these years, with a huge effort dedicated by the European (ESA) and USA (NASA) agencies for development of space based observatories dedicated to this purpose. Thanks to these missions (Kepler, TESS, CHEOPS, PLATO, ARIEL) we are now able not only to find new exoplanets, but also measure their radius, mass, therefore density and estimate their bulk composition, as well as study their atmosphere basic properties and composition.
For the closest to the Earth systems, there are projects to send a cluster of microchips launched at 0.2 times the light speed for direct investigation of their planets (Breakthrough program).
The student enrolled on this theme will be inserted into one of the ESA space mission programs (CHEOPS, PLATO or ARIEL), depending on her/his expertise/interests, with a possibility to also participate in the Breakthrough project.

(3E) Analysis of planetary data acquired by remote sensing and radar instruments

Funding institution: University of Trento
Doctoral site: Trento
Contact: Lorenzo Bruzzone (lorenzo.bruzzone [at] unitn.it)

Space missions for Earth observation and planetary exploration are of crucial importance for the huge scientific and technological return associated with them. Some of the most challenging science objectives of these missions require the analysis of the large amount of data acquired by the different instruments present in the mission payload. To improve the capability of extracting the information from these data (either focusing on a single instrument or on the data acquired by different instruments), it is required to develop automatic techniques based on the most recent machine learning methodologies that can enable both the definition of a new generation of data analysis systems and new capabilities of exploitation of the big data acquired by satellite missions.

This PhD position is aimed at the development of novel methodologies and techniques for the analysis of data/images acquired by remote sensing and radar systems for improving the science return of planetary exploration and/or Earth observation missions. The research (which will be developed at the RSLab, Dept. of Information Engineering and Computer Science, University of Trento) will address the definition of a general framework for the development of data analysis methodologies based on artificial intelligence and deep learning that will be then applied to missions in which RSLab is involved (refer to https://rslab.disi.unitn.it for more details).