Stages 2024

Every year the L2IT offers a limited number of internships (stages) to outstanding master students (M1 and M2) and students at écoles d’ingénieurs interested in undertaking a research project in one of the main research teams of the lab (particle physics, gravitational waves, nuclear physics, scientific computing and data). These internships allow students to work together with leading researchers on some of the most exciting topics in fundamental physics, exposing them to the most advanced theoretical, computational, observational and instrumental methods currently used in large-scale international experiments, in particular LISA, Virgo and ATLAS. Students who successfully complete a research internship at L2IT usually greatly improve their chances to be selected for a PhD programme if they decide to continue their studies. The L2IT itself offers at least one PhD position per year. 

The L2IT also welcomes one or two bachelor students (L3) per year who have the possibility to do a short research internship as part of their curriculum of studies.

The working language for research activities at L2IT is English. Students are expected to possess an acceptable level of English to apply for an internship at L2IT.

If you have any questions or need further information, please feel free to contact any member of L2IT (see list of current members).

All our internship offers for the spring-summer 2024 period are filled.


Application process

If you are a motivated student interested to apply for a research internship at the L2IT, please send the following documents to the head of the research group in which you would like to carry out your internship (see below for names and contacts):

      • a CV
      • a document listing the results of all your university exams;
      • a motivation letter (max one page).

The application deadline to send these documents is 21 November 2023.

Applications will be accepted until the positions are filled, but please note that a selection process will take place immediately afterwards this deadline. Few candidates will be selected for remote interviews at the beginning of December. Interviews can be held either in French or in English according to the candidate’s preference, but in any case please be prepared to have your English level tested during the interview. 

Contacts

Please send your applications and inquiries to the following persons:

Examples of internship projects

Here are some examples of internship research projects currently offered at L2IT. Please do not hesitate to mention one or more of these projects in your application if you are interested in them. For more information please feel free to contact members of the L2IT.

  • Geometric deep learning for high-energy particle tracking (M2 or final year engineering school)
    Computing, Algorithms and Data team, more information →
  • Bridging the gap: using spectroscopy to enhance gravitational wave cosmology
    Gravitational Waves team, more information →
  • Massive Black Holes in realistic LISA data: modified gravity or instrumental artifacts?
    Gravitational Waves team, more information →
  • Cosmology and Gravitational Waves: new tests of the standard cosmological model
    Gravitational Waves team, more information →
  • Exploring machine learning techniques to describe nuclear reactions
    Nuclear Physics team, more information →
  • Exploring nuclear matter under extreme conditions with particle correlations
    Nuclear Physics team, more information →
  • Development of a Monte Carlo simulation of multiple resonance decays and correlations in heavy-ion collisions
    Nuclear Physics team, more information →
  • Nuclear transport simulations for heavy-ion collisions and equation of state studies
    Nuclear Physics team, more information →
  • Particle Physics team
    Please get in touch with the team leader or any other senior member of the team

Details on the above listed subjects

| Computing, Algorithms and Data

Geometric deep learning for high-energy particle tracking
We are offering an internship opportunity for students pursuing a Master’s degree or in their final year of an engineering school program to join our Machine Learning Research and Development (ML R&D) team. This internship will concentrate on exploring novel Graph Neural Network architectures that operate in a multi-scale and multi-topological graph context, aimed at achieving faster and highly efficient particle track reconstruction.
Full description

| Gravitational Waves

Bridging the gap: using spectroscopy to enhance gravitational wave cosmology
One of the most significant challenges in cosmology is the difference in Hubble constant values resulting from different measurement methods. Gravitational waves (GWs) offer a third, independent approach to determine the Hubble constant and resolve this discrepancy. The key to employing GWs for cosmological purposes lies in the direct measurement of the source’s distance through GW signals, which can then be combined with the redshift of the galaxy from which the GW originated. Even when the exact host galaxy cannot be identified, considering all possible host candidates allows for a reliable estimate. By aggregating numerous such estimates from various GW events, we can progressively approach a resolution of the Hubble tension. During the ongoing observation period of the GW detector network, we are already detecting sources at distances where our knowledge of galaxies may not be detailed enough to provide an accurate Hubble constant estimate.
In this project, you will investigate the potential benefits of collaborating with astronomical telescopes to conduct spectroscopic observations, obtaining more precise redshift values for galaxies. You will learn how gravitational-wave cosmology works, what are the capabilities of the state-of-the-art telescopes, how to combine gravitational wave data with electromagnetic observations, and how to work in a large international collaboration. Based on this study, a partnership between the global gravitational-wave detector network and some of the world’s largest telescopes can start to be established. The internship will be undertaken in the GW group at the L2IT in Toulouse, which is composed by internationally well-known researchers, and currently counts 3 postdocs, 4 PhD students and 3 software engineers. Weekly interactions with group members and other L2IT members will expose the student to a highly dynamical environment where the she/he will be able to affine her/his research skills.

Massive Black Holes in realistic LISA data: modified gravity or instrumental artifacts ?
LISA is a future space-based detector that will fly in the mid-2030s and detect gravitational waves at low frequencies, targeting massive black hole binaries with masses of millions of solar masses. These signals will be extremely loud compared to the detections of stellar-mass black holes by LIGO/Virgo, and LISA will bring us in an era of high-precision gravitational-wave astronomy, enabling tests of general relativity (GR) with an unprecedented precision. However, most simulations of LISA data analysis work with an idealized instrument. In reality, the data will be complex, with non-stationarities and glitches, and with superposed signals. Hence the question we will address in this internship: could we mistake superposed signals or instrumental artefacts with deviations from GR ? Can we design workarounds in our analysis, to unleash LISA’s full potential ?
The internship will be undertaken in the GW group at the L2IT in Toulouse, which is composed by internationally well-known researchers, and currently counts 3 postdocs, 4 PhD students and 3 software engineers. Weekly interactions with group members and other L2IT members will expose the student to a highly dynamical environment where the she/he will be able to affine her/his research skills.

Cosmology and Gravitational Waves: new tests of the standard cosmological model
Gravitational waves constitute a new observational instruments which convey new information about our Universe and its structures in a completely complementary way with respect to standard electromagnetic observations. In particular gravitational waves emitted by the mergers of black hole and neutron star binaries can be used to test how fast the universe expands at different epochs of its evolution. Consequently different cosmological models can be tested with gravitational waves, with new possible insights into the contemporary mysteries of the Universe such as dark energy, dark matter, the Hubble tension, and others.
This internship project aims at investigating standard and alternative scenarios describing the evolution of our Universe using gravitational-wave observations from current and next generation gravitational-wave observatories. The student will become familiar with the basics of the theory of gravitational waves and with Bayesian statistical inference, she/he will get acquainted with some of the advanced theoretical and computational state-of-the-art techniques used in gravitational-wave cosmology. She/he will also have the opportunity to work within the framework of large international collaborations dedicated to observe gravitational waves, in particular the LIGO-Virgo-KAGRA Collaboration, the LISA Consortium and the Einstein Telescope Consortium. The internship will be undertaken in the GW group at the L2IT in Toulouse, which is composed by internationally well-known researchers, and currently counts 3 postdocs, 4 PhD students and 3 software engineers. Weekly interactions with group members and other L2IT members will expose the student to a highly dynamical environment where the she/he will be able to affine her/his research skills.

| Nuclear Physics (and ML techniques)

Exploring machine learning techniques to describe nuclear reactions
The description of nuclear reactions is important to understand the properties of nuclei and unravel the interplay between the structure and dynamics. Insights into these reactions are required to obtain a good comprehension of the mechanisms leading to the synthesis of new super-heavy elements and to understand the origin of the elements formed in the stars.
State-of-the-art theoretical calculations (Time-dependent Density functional theory) offer a microscopical description of these reactions and more generally the nuclear dynamics. However, they require a large computational time limiting the range of applicability. Machine learning models can circumvent these limitations by providing surrogate models (a model fitted on another model) to perform large-scale calculations. The fast model can then be applied to integrate over all the initial degrees of freedom (impact parameter, orientation of the deformed nuclei).
The student will evaluate the accuracy of the machine learning model. Depending on his/her background and interest, he/she will have the opportunity to either: 
– Explore new machine-learning techniques to improve the model. Testing different architecture, learning techniques…
– Investigate new physical applications with the current surrogate model. This includes the fusion cross-section calculations, quasi-fission, multi-nucleon transfer reactions, and giant resonances
Full description ↗

Exploring nuclear matter under extreme conditions with particle correlations
Heavy-ion collisions (HIC) allow us to study how nuclear matter behaves under extreme conditions of temperature and pressure, namely studying the so-called Equation of State (EoS). This field is one of the most important in the nuclear physics community due to its  implications on our understanding of nucleon-nucleon interactions as well as on the physics of neutron stars and other astrophysical phenomena phenomena. These studies are conducted with experiments performed at the Grand Accelerateur National d’Ions Lourds (GANIL) in France, and at other international facilities that are capable of producing beams of nuclei at intermediate energies (E/A=30-100 MeV). The analysis of collected data with multi-detector arrays allow us to study correlation functions (CF) between detected particles whose momentum vectors are precisely measured.
The student will be involved in developing analysis algorithms to study particle-particle correlations, using large data sets from experiments performed at GANIL (France) and at NSCL (USA). The goal consists in studying the production and decay of resonances in a medium con nucleons and clusters which is hot and at denotes way from saturation. These resonances correspond to the production of exotic and short-lived nuclear states whose properties allow us to learn about the space-time and the thermodynamical properties of nuclear systems and their links to the nuclear EoS.

Development of a Monte Carlo simulation of multiple resonance decays and correlations in heavy-ion collisions
One of the most spectacular phenomena observed in the study of heavy-ion collisions is the observation of several unbound states that are produced for a very short time and decay during the dynamical evolution of the system. These decays are identified with multi-particle correlation spectroscopy (by measuring the multi-body invariant mass of the decay channel) and can provide information on both thermodynamic properties of the system and nuclear structure as it evolves in the dilute and hot nuclear medium. 
The student will work on developing a Monte Carlo simulation of multiple decay of resonances in a nuclear system at different temperatures and characterised by collective motion, deformations, low densities and multi-fragment breakup configuration. The simulation will be constructed with a direct interface to existing experimental data collected at GANIL and at other laboratories.

Nuclear transport simulations for heavy-ion collisions and equation of state studies
Collisions between nuclei at low, intermediate an relativistic energies allow one to explore the properties on the in-medium nucleon-nucleon interaction and explore the nuclear equation of state.  In this project, the student will be familiarised with the use of some of the most important models of heavy-ion collision simulation, based on different approaches. These models provide predictions for observables that are directly linked to unknown ingredients of the interaction and of the equation of state. Such predictions are then filtered with the acceptance of experimental setup to understand to what extent they can be measured in experiments. On the intermediate and relativistic energy side (E/A>20 MeV), the FAZIA collaboration is seeking to produce a database of simulated observables in order to understand existing data collected at GANIL and plan possible future campaigns at higher energy facilities, such as FRIB in the USA. These higher energy investigations are of particular importance for their link to the properties of neutron stars.  On the lower energy side, models provide important links to fundamental nuclear physics quantities that are still needed, especially in view of the future availability of radioactive beams at the Spiral2-GANIL facility.

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