Research topics of the doctorate

PhD Scholarship Title Molecular astrophysics: challenging reactivity beyond the second period elements via ion-molecule reactions
Research group link https://www.physics.unitn.it/98/fisica-atomica-e-molecolare
Contacts: Daniela Ascenzi daniela.ascenzi [at] unitn.it, Paolo Tosi paolo.tosi [at] unitn.it (lab. FAM), Ines Mancini ines.mancini [at] unitn.it (lab. Chimica Bioorganica)
Synthetic description of the activity and expected research outcome The number of molecules detected in space is increasing at a fast pace thanks to the improved sensitivities of telescopes. The presence of complex molecules in regions with extreme temperature and pressure conditions is a great challenge to the comprehension of chemical reactivity. By using an interdisciplinary approach (physics/chemistry/astronomical observations) the project aims at unveiling the formation routes of molecules containing atoms beyond the second period of the Periodic Table (e.g. S, P, Si and Cl). The research will focus on the reactivity of charges species with neutrals using guided ion beam mass spectrometry (also carried out at SOLEIL synchrotron radiation facility).

PhD Scholarship Title Relaxation dynamics of glasses and supercooled liquids
Research group link https://www.physics.unitn.it/105/struttura-e-dinamica-dei-sistemi-complessi
Contacts: prof. Giacomo Baldi Giacomo.baldi [at] unitn.it
Synthetic description of the activity and expected research outcomeStructural glasses are often considered as archetypes of out-of-equilibrium materials. The proposed activity will focus on the relaxation dynamics of chalcogenide and oxide glasses prepared either under normal ambient conditions or pre-densified with the application of high pressures. Relaxation processes will be monitored by a combination of experimental methods, including laboratory based spectroscopic and calorimetric techniques and advanced X-ray spectroscopies at large scale facilities. The thesis will be held in co-tutoring between the University of Trento and the University of Lyon 1 and the PhD candidate, if successful, will have a PhD degree of both institutions.

PhD Scholarship Title Theory of ultrafast photoinduced phases in technology relevant materials
Research group link https://webapps.unitn.it/du/it/Persona/PER0195318/Pubblicazioni , https://mcalandra.github.io/
Contacts: prof. Matteo Calandra Buonaura m.calandrabuonaura [at] unitn.it
Synthetic description of the activity and expected research outcomeUltrafast lasers sources open new perspectives in exploring broken symmetry phases as it becomes possible to promote a substantial number of electrons in excited states generating a thermalized electron-hole plasma and leading to reversible or irreversible phase transitions. Light-induced charge density waves, order-disorder transitions, melting, stabilization of topological phases and laser-tunable ferroelectricity have been demonstrated. Experiments are far ahead of theory as few (if any) of the demonstrated light-induced phenomena have been predicted by theory. In this thesis we plan to develop a theoretical strategy to predict and discover photoinduced phases in materials. To accomplish this goal, we will develop quantum-chemical and molecular dynamics schemes including the effect of the thermalized electron-hole plasma on the crystal potential and accounting for light-induced non-perturbative quantum anharmonicity. We will try to answer questions such as: which systems undergo light induced phase transitions? Can we use light pulses to enhance or tune charge density wave, ferroelectric and magnetic critical temperatures, to generate new topological phases or to optimize the properties of thermoelectric materials? The proposal will impact chemistry, physics, energy and material engineering. It could lead, for example, to the development of devices with dynamical light switching on/off of magnetism or ferroelectricity, relevant for ultrafast memories, or to the stabilization of new thermoelectric compounds with photo-tunable thermal conductivity and figure of merit.

PhD Scholarship Title Kinetics of soft matter systems: from statistical mechanics to machine learning
Research group link https://sbp.physics.unitn.it/raffaello-potestio/
Contacts: prof. Raffaello Potestio raffaello.potestio [at] unitn.it
Synthetic description of the activity and expected research outcomeThe position is funded through the FARE Ricerca in Italia - R18ZHWY3NC HAMMOCK (CUP E64I19003120001) project supported by the Italian Ministry of University and Research. The aim of the project is to understand the relation between the kinetic properties of coarse-grained models of soft matter systems and their high-resolution counterpart. The successful candidate will apply the toolbox of statistical mechanics, information theory, and deep learning to gain greater insight into this relation, so as to comprehend the function of macromolecules and model biological systems in and out of equilibrium, and to highlight general principles to guide the design of artificial systems and materials with desired properties.
Ideal candidate (skills and competencies): Background in physics, chemistry, mathematics, engineering. Excellent programming skills (unix os, C/C++, python, matlab, tensorflow)

PhD Scholarship Title Photonic neural networks for optical communications
Research group link http://nanolab.physics.unitn.it/index.php
Contacts: prof. Lorenzo Pavesi lorenzo.pavesi [at] unitn.it, Mattia Mancinelli mattia.mancinelli [at] unitn.it
Synthetic description of the activity and expected research outcomeArtificial Neural Networks (ANN) are computational network models that mimic how biological neurons elaborate data. These models have dramatically improved the performance of many learning tasks, including speech and object recognition. The scientific community developed specific electronic architectures that directly behave as an ANN trying to improve the computational speed and energy efficiency. Photonics already boosted the telecom field to a new performance level by exploiting the huge data handling capabilities, speed, and flexibility of optical fibers. The same paradigm is going to be applied to the ANN. The project is inserted in this context where optics will be exploited to find new ways to correct distortion in optical signals that propagate in optical fiber. The aim of the research is the development, simulation, and testing of a neural network chip to mitigate optical nonlinearities in optical fibers. The activity will comprehend the system transmission simulation (with and without the neural network), the neural network simulation, the test of the fabricated circuits, the setup of the testing system, and the validation of the neural network mitigation action in high-frequency transmission experiments which will comprehend multiple fiber spans and different data format. The objective is to demonstrate that photonic neural networks are able to mitigate fiber optic nonlinearities at a high transmission rate. Different protocols will be used to encode the data in order to increase the transmission rates and the benefit of the protocol. This PhD will be part of the ERC-funded BACKUP project (P.I. Prof. Lorenzo Pavesi, Dept. of Physics). More info at https://r1.unitn.it/back-up/
Ideal candidate (skills and competencies): We are seeking a highly motivated and passionate student, with a strong attitude to work in a collaborative and interdisciplinary team, and with a background in photonics and, possibly, in machine learning.

PhD Scholarship Title Theory of ultrafast phase transitions
Research group link https://webapps.unitn.it/du/it/Persona/PER0195318/Pubblicazioni , https://mcalandra.github.io/
Contacts: prof. Matteo Calandra Buonaura m.calandrabuonaura [at] unitn.it
Synthetic description of the activity and expected research outcomeFemtoseconds laser can be used to promote charge density waves, order/disorder phase transitions, the non-thermal melting of solids and many other broken symmetry states. However a complete theoretical understanding for the occurrence of these broken symmetry states after ultrafast light irradiation is missing. We will develop a therotical framework to study and predict possible phase transitions in order to spot relevant photoinduced phases and new exotic phase of matters induced by light (thermoelectricity, ferroelectricity, magnetism,amorphous systems with special properties). Moreover, we will develop a consistent scheme to spot materials in which such kind of transition can take place. Ideal applications will be bulk systems close to structural transitions and 2D materials.
Ideal candidate (skills and competencies): Passion for theory and computational approaches, good knowledge of quantum mechanics of solid state theory. Knowledge of ab-initio of many body perturbation theory codes will be a plus (albeit it is not necessary as the candidate can learn these techniques in the theory group at uniTN).

PhD Scholarship Title Quantum many-body systems and ultracold gases
Research group link https://bec.science.unitn.it/BEC/0_Home.html
Contacts: prof. Gabriele Ferrari gabriele.ferrari [at] unitn.it
Synthetic description of the activity and expected research outcomeUltracold atomic gases offer a flexible platform to address open problems in fundamental physics such as many-body properties in quantum gases, transport phenomena, quantum simulation of fundamental interactions and gauge fields. The PhD student will work within the interdisciplinary environment of the BEC Center (https://bec.science.unitn.it/BEC/0_Home.html) where research both on theory and experiments is done covering a wide range of themes.
Ideal candidate (skills and competencies): The ideal candidate should possess good knowledge of quantum mechanics, statistical physics, atomic physics with applications to data analysis and experimental research. The PhD student will work within the interdisciplinary environment of the BEC Center ((https://bec.science.unitn.it/BEC/0_Home.html) where research both on theory and experiments is done covering a wide range of themes.

PhD Scholarship Title Quantum-classical hybrid algorithms for real-world inspired application problems using qudits
Research group link https://hauke-group.physics.unitn.it/
Contacts: prof. Philipp Hauke (University of Trento), dr. Sebastian Schmitt (Honda Research Institute Europe GmbH)
Synthetic description of the activity and expected research outcomeDespite fascinating recent advancements in quantum computers, there are central impediments for their widespread deployment. In particular, there is the need of finding practical and useful applications as well as to overcome restrictions of the scalability of existing hardware. Existing quantum computation hardware employs qubits, i.e., two-state quantum systems. A very promising and much less researched alternative is given by multi-level quantum systems, so-called qudits. In principle, qudits allow for more efficient and error-tolerant quantum computation [1]. Yet, qudit quantum computing is a hitherto little researched topic on the level of hardware (e.g., [2-4]) as well as quantum algorithms (e.g., [5,6]). The aim of this PhD work is to make significant advances towards qudit quantum computing. We will investigate the application of hybrid quantum-classical optimization algorithms to industry-inspired optimization problems, e.g., from the scheduling or energy management domain. Here, an important aspect will be the inclusion of constraints as are typically found for industry-relevant problems [6]. A further focus is the theoretical investigation of quantum platforms (ultracold atoms, trapped ions, superconducting qubits) that can naturally realize qudit systems, potentially in collaboration with leading experimental groups. The project will be co-supervised by Honda Research Institute Europe GmbH, which will also ensure the relevance of the considered problems for actual problems from an industry environment. The PhD work will open the door to exploiting an alternative paradigm for quantum computing, leading to increased efficiency and relevant application algorithms.
Literature
[1] See, e.g., https://spectrum.ieee.org/tech-talk/computing/hardware/qudits-the-real-f...
[2] Kues, et al., On-chip generation of high-dimensional entangled quantum states and their coherent control, Nature 546, 622–626 (2017).
[3] Ringbauer, et al., A universal qudit quantum processor with trapped ions, arXiv:2109.06903
[4] Weggemans, et al., Solving correlation clustering with QAOA and a Rydberg qudit system: a full-stack approach, arXiv:2106.11672 (2021)
[5] Kasper, et al. Universal quantum computation and quantum error correction with ultracold atomic mixtures, Quantum Sci. Technol. 7 015008
[6] Deller, et al., Quantum approximate optimization algorithm with qudits, in preparation (2021)
Ideal candidate (skills and competencies): The ideal candidate has a strong background in quantum mechanics, in particular with courses on quantum information and quantum computing, as well as related subjects such as quantum optics, atomic physics, classical information theory, and numerical optimization. Furthermore, strong analytical and computational skills are required. He/she should have a high interest in interdisciplinary research questions.

PhD Scholarship Title Particle, astroparticle, nuclear, theoretical physics, related technologies and applications, including medical Physics
Research group link INFN
Contacts: for further information on the possible research topics see www.infn.it or contact Rita Dolesi for experimental Physics (Rita.Dolesi [at] unitn.it ); Francesco Pederiva for theoretical Physics (Francesco.Pederiva [at] unitn.it) Chiara La Tessa for applied and medical physics (chiara.latessa [at] unitn.it)
Synthetic description of the activity and expected research outcomeThe thesis topics will be selected within the many areas of forefront research pursued at Trento Institute for Fundamental Physics and Applications (TIFPA) of INFN. Current main activities include:
1) experimental particle and astroparticle Physics,
2) experimental gravitation both earth and space based,
3) gravitational wave astronomy,
4) antimatter related experiments,
5) R&D on particle and radiation detectors and other solid state quantum micro devices, 6) computational Physics and AstroPhysics,
7) theory of fundamental interactions,
8) theoretical cosmology,
9) medical physics applied to therapy with high energy charged particles.

PhD Scholarship Title Development of a payload for differential flux measurement of low energy particles in space
Research group link https://sd.fbk.eu/en/research/custom-radiation-sensors-crs/
Contacts: dr. Giancarlo Pepponi (FBK) pepponi [at] fbk.eu, prof. Francesco Nozzoli (TIFPA)
Synthetic description of the activity and expected research outcome Precise monitoring of the highly dynamic space radiation environment around Earth is crucial for spacecraft safety. It supports development of solar particle flux models and allows studies of space weather and of the interaction of radiation belts with Earth's lithosphere. The project activities include the study of a flat detection geometry to reduce the size of the low energy particle detector. The project also includes the parametric characterization of the sensors, the development as well as testing with particle beams of a detector prototype and more in general the integration of the payload.

PhD Scholarship Title Deep Learning for event selection at the LHC
Research group link https://www.physics.unitn.it/en/237/astro-particle-physics
Contacts: prof. Roberto Iuppa roberto.iuppa [at] unitn.it, prof. Marco Cristoforetti marco.cristoforetti [at] fbk.eu
Synthetic description of the activity and expected research outcomeThe LHC experiments produce about 90 petabytes of data per year. Inferring the nature of particles produced in high-energy collisions is crucial for both probing the Standard Model with greater precision and searching for phenomena beyond the Standard Model. In this context, event selection is becoming more difficult than ever before and requires expertise at the border between physics and computer science. During the PhD the student will be guided in exploring and designing Deep Learning algorithms to tackle this problem learning how to apply rigorous Data Science methodologies. The activity will be carried out in collaboration with INFN-TIFPA, Fondazione Bruno Kessler and within the ATLAS experiment at the LHC. Candidates familiar with High Energy Physics are welcome, and basic knowledge of Machine Learning/Deep Learning is recommended.
Ideal candidate (skills and competencies): Basic knowledge of particle physics. Basic skills of scientific programming.

Topic: Measurement of antiproton production cross section in p-He collisions with the AMBER experiment at CERN
Research group link: https://www.tifpa.infn.it/projects/ams-02/ , https://www.physics.unitn.it/en/237/astro-particle-physics , https://nqf-m2.web.cern.ch
Contacts: Paolo Zuccon paolo.zuccon [at] unitn.it
Synthetic description of the activity and expected research outcome: Cosmic Rays are a powerful tool for the investigation of exotic physics/astrophysics in space. As an example, an excess of antiprotons in cosmic rays might be a signature of Dark Matter annihilation in our galaxy, however some antiprotons are present in the cosmic ray flux since they are produced by collisions of primary protons and p/He nuclei with the Inter Stellar Medium. The AMS magnetic spectrometer measured the antiproton spectrum in the cosmic rays up to 525 GeV energy. To search for a Dark Matter contribution one must compare the AMS measurement with the predictions of the secondary antiproton background. However the current knowledge of the antiproton production cross section in the p-p and p-He collisions, put an uncertainty on the background estimation that is larger than AMS measurements one. The AMBER experiment at the CERN Super Proton Synchrotron will accurately measure the p-p and p-He inelastic cross sections for antiproton production. Therefore AMBER will provide a fundamental ingredient for the search of Dark Matter annihilation the galaxy. The student will be involved in the preparation of the AMBER experiment, the preliminary measurement run foreseen for 2023 and/or in the data analysis.
Ideal candidate (skills and competencies): The ideal candidate should possess problem solving skills and should be available to spend some period at CERN. Knowledge of C++ or Python programming language.

Topic: Measurement of isotopic composition of nuclei in cosmic rays
Research group link: https://www.tifpa.infn.it/projects/ams-02/ , https://ams02.space/
Contacts: Paolo Zuccon paolo.zuccon [at] unitn.it
Synthetic description of the activity and expected research outcome: Cosmic Rays are a powerful tool for the investigation of exotic physics/astrophysics in space. In particular the ratio (and energy distribution) of primary nuclei (i.e. the nuclei directly produced by the high energy astrophysical sources) over the secondary nuclei (produced by the collision of primary nuclei with the Inter Stellar Medium) provides valuable information about the propagation mechanism of cosmic rays, the production of secondary anti-matter and the structure of our galaxy. With its unprecedented statistics (>200 billion events collected on the International Space Station) and powerful particle identification capability, the AMS spectrometer can measure the rarest components of cosmic rays exploring high energy region. The candidate will join the AMS-Italy group for this challenging data analysis (big data mining with development of machine learning algorithms) and contributing to AMS data taking and analysis at CERN.
Ideal candidate (skills and competencies): The ideal candidate should possess problem solving skills and should be available to spend some period at CERN. Knowledge of C++ or Python programming language.

Topic: An integral approach to space based monitoring of geophysical phenomena from space
Research group link: Astroparticle physics in space (APP Laboratory)
Contacts: Prof. Roberto Battiston roberto.battiston [at] unint.it
Synthetic description of the activity and expected research outcome: The CSES satellite constellation will be operational starting on mid 2023 with the scheduled launch of the second CSES satellite. This will be the first constellation ever developed to monitor geophysical fast changes (earth-quakes, tsunamis, volcanos) in near real time, based on a new kind of re-mote sensing using non-imaging physical observable. The PhD student will have access to unique new data from the two orbiting satellites with the goal of designing an optimal multi satellite constellation devoted to this new type of remote sensing.
Ideal candidate (skills and competencies): She/he should be Interested in data analysis, curious and interested to contribute to the development of a new multidisciplinary field of research, ranging across particle physics, plasma physics, solar physics, physics, and mathematical modeling of the Earth—Magnetosphere interactions.

Topic: Supramolecular topological soft materials
Research group link: https://sites.google.com/g.unitn.it/sbp
Contacts: Luca Tubiana luca.tubiana [at] unitn.it
Synthetic description of the activity and expected research outcome: Topological soft materials made of interlocked polymer rings constitute a new class of substances with exceptional physical properties such as high resistance to deformations, precise and controllable response functions, shape memory. Those characteristics make them ideal candidates for the development of smart materials to be used in sensors, batteries, selective filters for the removal of heavy metals from water. The purpose of the project is to characterize computationally the interplay between the topological and physical properties of systems made of interlocked rings; how such systems can be self-assembled from some standard building blocks; their potential use as selective filters for heavy metal ions.
Ideal candidate (skills and competencies): A strong passion for interdisciplinary research at the frontier be-tween statistical physics, biology, and material science. Background in either physics, chemistry, mathematics, or engineer-ing. A strong interest in computational and statistical approaches to problem solving.

Topic: Multimessenger signals from compact binary mergers
Research group link: albinoperego.eu
Contacts: Albino Perego albino.perego [at] unitn.it
Synthetic description of the activity and expected research outcome: The merger of two neutron stars is a extreme astrophysical event in which all fundamental interactions play a pivotal role. The modelling of such an event is one of the most challenging tasks in present theoretical physics and astrophysics. However, due to the advent of gravitational waves detectors and multimessenger astrophysics, it is also one of the most vibrant and lively research topics. Matter expelled during the merger undergoes r-process nucleosynthesis and produces the heaviest elements in the universe. Moreover, this radioactive material, possibly in association with a relativistic jet, produces a series of peculiar electromagnetic emissions, including gamma-ray bursts and kilonovae. The topic of this PhD project is the study of the matter ejection and r-process nucleosynthesis in binary neutron star mergers, and of the subsequent production of electromagnetic transients. In particular, the project will connect results from the latest binary neutron star merger simulations with the nuclear physics of neutron rich nuclei, with radiative and thermalization processes in magnetized astrophysical plasma. The expected outcome will be the prediction of nuclear abundances, light curves and spectra grounded on some of the most advanced merger models. Another possible subtopic will be the production of a reduced nuclear network for r-process nucleosynthesis, possibly in combination with Machine Learning techniques.
Ideal candidate (skills and competencies): The project has a strong physical and theoretical connotation, with also a significant computational aspect. The candidate will work in close collaboration with the advisor and with a small size community of international collaborators. The ideal candidate should have: - a strong background in the physics and astrophysics of compact objects, or on nuclear astrophysics or in theoretical astrophysics; - a good background in computational physics, with a special emphasis on Python; a certain knowledge in low level programming languages like C, C++ or Fortran is also welcome; - possibly, a good theoretical background, including General Relativity and/or particle and nuclear physicsß

Topic: Modelling of compact binary mergers in numerical relativity
Research group link: albinoperego.eu
Contacts: Albino Perego albino.perego [at] unitn.it
Synthetic description of the activity and expected research outcome: The merger of two neutron stars is a extreme astrophysical event in which all fundamental interactions play a pivotal role. The modelling of such an event is one of the most challenging tasks in present theoretical physics and astrophysics. However, due to the advent of gravitational waves detectors and multimessenger astrophysics, it is also one of the most vibrant and lively research topics.
State of the art models of binary neutrons star mergers require the solution of general relativistic radiation hydrodynamics equations for nuclear matter. Despite their central role, the modelling of neutrinos in mergers is still in its infancy. The aim of this PhD project is to significantly improve the microphysical content of present Numerical Relativity codes by introducing detailed neutrino interactions and applying them to radiative transport scheme. The final goal will be the detailed study of the merger dynamics in the presence of neutrinos and of their impact on its many observables, including the stability of the remnant and the properties of the matter expelled from the merger (ejecta).
Ideal candidate (skills and competencies): The project has both a strong numerical and physical connotation. The candidate will work in close collaboration with the advisor and with a small size community of international collaborators.
The ideal candidate should have:
- a strong theoretical background, including General Relativity and/or particle and nuclear physics,
- a good background in computational physics, with a special emphasis on low level programming languages like C, C++ or Fortran. Additionally, a good knowledge of Python is also welcome;
- possibly, a background in the physics and astrophysics of compact objects, or nuclear astrophysics.

Topic: Multi-scale investigation of protein/nucleic acids macromolecular complexes
Research group link: https://sites.google.com/g.unitn.it/sbp
Contacts: Gianluca Lattanzi gianluca.lattanzi [at] unitn.it
Synthetic description of the activity and expected research outcome: New experimental tools are providing evidence for a complex network of interactions involving protein assemblies and nucleic acids. This evidence is always accompanied by hypotheses on the mechanical transduction system that convey information from the binding site to other regions of the macromolecular complex. However, these hypotheses can nowadays be tested on reliable and multi-scale computational models, on which our group has developed a consistent expertise. The idea of this project is to concentrate mainly on two systems: one is the CRISPR/Cas9 macromolecular complex, that constitutes the adaptive immune system of many prokaryotes and has been recently exploited to obtain a gene-editing biotechnological tool. A possible second system involves the human ribosome and its interactions with regulating or modulating proteins. In both cases, the goal of the project is to investigate the communication pathways between regions of the macromolecular complexes and point out the residues that may play a pivotal role in this respect. Several methods will be employed, including atomistic molecular dynamics simulations of the entire complexes, coarse graining strategies and models, enhanced sampling techniques. Data analysis based on machine learning algorithms may complement the competencies already available within the group. The expected research outcome is a computational protocol aimed at investigating protein/nucleic acids macromolecular complexes and respond in due time to questions posed by experimental data.
Ideal candidate (skills and competencies): Good programming skills and desire to attend courses in computational physics and data science. Solid competencies in statistical mechanics.

Topic: Gravitational wave data Analysis: interpretation of transient sources using generic assumptions on their dynamics.
Research group link: https://www.physics.unitn.it/en/78/experimental-gravitation
Contacts: Giovanni Andrea Prodi giovanniandrea.prodi [at] unitn.it, Francesco Salemi francesco.salemi [at] unitn.it
Synthetic description of the activity and expected research outcome: The more general searches for gravitational wave transients are able to provide a morphological description of detected signals using a minimal set of assumptions. This activity aims to extend the capabilities of these general methods to the interpretation of the underlying dynamics of the source. Investigated techniques will include physics-informed machine learning, which has just been proposed this year for gravitational wave data analysis and promise to be computationally efficient. The methods will be tested on actual data of LIGO-Virgo-KAGRA detectors and on simulated data of next generation detectors. Once successful, these methods will be crucial crucial discovery tools in gravitational wave astronomy, enabling a fast disambiguation of overlapped transient events as well as a rapid selection of the more interesting ones for multi-messenger observations and follow-up studies. The candidate will become member of the LIGO-Virgo-KAGRA and Einstein Telescope collaborations.
Ideal candidate (skills and competencies): The ideal candidate has good programming skills and basic competences in statistics and gravitational wave science.

Topic: Gravitational Wave Data Analysis: methods and searches for weak signals and features
Research group link: https://www.physics.unitn.it/en/78/experimental-gravitation
Contacts: Giovanni Andrea Prodi giovanniandrea.prodi [at] unitn.it, Francesco Salemi francesco.salemi [at] unitn.it
Synthetic description of the activity and expected research outcome: The activity will target the development of data analysis methods to search and characterize weak signals or rare features in the upcoming observations of gravitational wave detectors (2023). The observations will be interpreted by comparing with simulations based on alternative models. Possible cutting edge examples include investigations of the still unknown population of Intermediate Mass Black Holes (directly observed for the first time in 2019), tests of General Relativity on the emission from Black Holes, quest for the expected astrophysical foreground from unresolved compact binary coalescences. The candidate will become member of the LIGO-Virgo-KAGRA collaborations.
Ideal candidate (skills and competencies): The ideal candidate has programming skills and basic competences in statistics and gravitational wave science.

Topic: Mode-matching Sensing for Gravitational Wave detectors
Research group link: http://public.virgo-gw.eu/ , http://www.et-gw.eu/
Contacts: Antonio Perreca antonio.perreca [at] unitn.it
Synthetic description of the activity and expected research outcome: One of the highest scientific moments of the last century was touched when the LIGO interferometer detected the first gravitational wave signal on September 14th, 2015. The LIGO-Virgo collaboration announced this astonishing result in the following February 2016, opening a new way to look at the universe. Since the first detection, more than 90 events have been detected, including signals originated from binary black holes, binary neutron stars and Neutron Star-Black Hole mergers. The LIGO/Virgo/KAGRA Scientific Collaboration is implementing new techniques to increase the sensitivity of the current and the next generation of gravitational wave detectors. The higher is the sensitivity and the further can be the origin of the detected signals, leading to a higher rate of detection and to a deeper knowledge of the universe. The limitations of the new upgrades are due to the optical losses, namely losses due to mode-matching between optical cavities. Conventional beam-profiling techniques measure mode-matching with limited precision. To scale down the limitations due to the optical losses sensing systems and adaptive optics are required. The first are used to measure the losses and the second to reduce the losses correcting the laser beam parameters. Moreover, the techniques will also be explored in the future Einstein Telescope (ET) experiment. The Virgo-ET Gravitational wave group at the University of Trento will develop new techniques to sense and correct mode matching in optical cavities.
Ideal candidate (skills and competencies): The candidate will be part of the LIGO/Virgo/KAGRA and ET collaborations. He will be responsible for developing a system able to sense the optical mode matching in an optical cavity with the use of a Mode Converter Telescope. He will learn to design and realize a table-top experiment, dealing with optics, electronics, control systems and software for optical simulations. The system will be implemented in the Advanced Virgo detector. The candidate will also be involved actively in the commissioning activities on the Virgo detector site and in the simulation activities for Einstein Telescope.

Topic: Light shaping for Gravitational Wave detectors
Research group link: http://public.virgo-gw.eu/ , http://www.et-gw.eu/
Contacts: Antonio Perreca antonio.perreca [at] unitn.it
Synthetic description of the activity and expected research outcome: One of the highest scientific moments of the last century was touched when the LIGO interferometer detected the first gravitational wave signal on September 14th, 2015. The LIGO-Virgo collaboration announced this astonishing result in the following February 2016, opening a new way to look at the universe. Since the first detection, more than 90 events have been detected, including signals originated from binary black holes, binary neutron stars and Neutron Star-Black Hole mergers. The LIGO/Virgo/KAGRA Scientific Collaboration is implementing new techniques to increase the sensitivity of the current and the next generation of gravitational wave detectors. The higher is the sensitivity and the further can be the origin of the detected signals, leading to a higher rate of detection and to a deeper knowledge of the universe. The limitations of the new upgrades are due to the optical losses, namely losses due to mode-matching between optical cavities. Conventional beam-profiling techniques measure mode-matching with limited precision. To scale down the limitations due to the optical losses sensing systems and adaptive optics are required. The first are used to measure the losses and the second to reduce the losses correcting the laser beam parameters. Moreover, the techniques will also be explored in the future Einstein Telescope (ET) experiment. The Virgo-ET Gravitational wave group at the University of Trento will develop new techniques to sense and correct mode matching in optical cavities.
Ideal candidate (skills and competencies): The candidate will be part of the LIGO/Virgo/KAGRA and ET collaborations. He will be responsible for developing a system able to correct optical losses due to the mode matching in optical cavities. He will learn to design and realize a table-top experiment, dealing with optics, electronics and software for optical simulations. The system will be implemented in the Advanced Virgo detector. The candidate will also be involved actively in the commissioning activities on the Virgo detector and in the simulation activities for Einstein Telescope.

Topic: Photocatalytic remediation of contaminated waters: materials design, synthesis and field testing.
Research group link: IdEA Lab; https://www.physics.unitn.it/en/104/idea-hydrogen-energy-environment; http://idea.physics.unitn.it/
Contacts: Michele Orlandi: michele.orlandi [at] unitn.it, 0461282012
Synthetic description of the activity and expected research outcome: Water contamination by organic pollutants is one of the most serious environmental concerns today but also one that can be tackled by photocatalysis. The PhD student will: (1) design photocatalytic materials matching thermodynamics, optics and catalytic properties with application requirements; (2) synthesize them by using the most appropriate combination of physical and chemical methods; (3) design and implement a lab-scale system to evaluate the efficiency of the photocatalysis process under simulated or concentrated sunlight; (4) optimize and bring to proof-of-concept level a process for water decontamination from selected pollutants. The PhD student will be an integral part of the IdEA laboratory, a well-equipped multidisciplinary research group boasting decades of experience in the field. 
Ideal candidate (skills and competencies): Experimental Physics, Solid state physics, Materials Physics and Chemistry, Nanomaterials, General and Inorganic Chemistry.

Topic: Exceptional point sensing
Research group link: http://nanolab.physics.unitn.it/index.php
Contacts: Lorenzo Pavesi lorenzo.pavesi [at] unitn.it 0461/281605, Stefano Biasi stefano.biasi [at] unitn.it
Synthetic description of the activity and expected research outcome: In integrated photonics, non-Hermitian systems show degeneracies which can be used to develop topological systems and novel sensors. In this thesis, based on integrated silicon photonics, the physics of non-hermitian microresonators arranged in topological matrices will be experimentally studied and theoretically modelled. The novel properties of the systems will be experimented with the aim to show novel devices such as unidirectional emitters, exceptional point sensors or optical insulators. More information at http://nanolab.physics.unitn.it/
Ideal candidate (skills and competencies): Expertise in integrated photonics

Topic: Addressing physical problems with information-theoretical methods
Research group link: https://nse.physics.unitn.it/
Contacts: Leonardo Ricci leonardo.ricci [at] unitn.it
Synthetic description of the activity and expected research outcome: Addressing physical problems with information-theoretical – i.e. entropy-based – methods is a thriving field. Entropy-based methods provide a complementary approach to more conventional and established analytical techniques. The final goal is to apply these methods to experiments ranging from neuroscience to climatology.
Ideal candidate (skills and competencies): Competencies in statistics, statistical physics, and signal and system analysis. Good knowledge of math. Ability to program in C++. An interest in electronics is also welcome.