Internships

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).

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 2022.

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.

| Computing, Algorithms and Data

  • GEOMETRIC DEEP LEARNING MEETS PARTICLES AT CERN
    We are looking for an outstanding intern to contribute to our development of innovative artificial intelligence algorithms, geometric deep learning, and more precisely graph neural networks (GNN) for the analysis of data of the international particle physics experiment ATLAS [1]. ATLAS is located at the Large Hadron Collider (LHC) at CERN. Its aim is to reveal the ultimate properties of matter. In 2028, the rate of collisions provided by the LHC to the ATLAS detector will be increased by an order of magnitude. This will allow the ATLAS experiment to study rare physics phenomena that are at the heart of today’s pressing questions in fundamental physics. Unfortunately the current algorithms will not be able to cope with the complexity and rate of the data recorded. New methods, including the use of AI-based techniques are explored by the ATLAS collaboration. The L2IT team is the world leader, with close collaborators in Berkley (US) and Illinois (US), in the development of a geometric deep learning technique that may solve the problem of the analysis of the data from the innermost part of the ATLAS detector (ITk, a new subsystem for charged particle tracking to be installed in 2028) [2-4]. The intern will be fully immersed in our team and contribute to the ongoing R&D project on GNN at L2IT. His/her work will focus on improving the performance of GNNs through the optimisation of the underlying parameters and architecture of our GNNs. The intern will be confronted with an international working environment. The internship will allow you to obtain strong skills in data analysis and innovative machine learning techniques. Access to high-performance computing facilities is provided.

[1] https://atlas.cern/
[2] https://doi.org/10.1051/epjconf/202125103047
[3] https://cds.cern.ch/record/2815578?ln=en
[4] https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PLOTS/IDTR-2022-01/

| Gravitational Waves

  • GRAVITATIONAL WAVE COSMOLOGY
    This internship project aims at investigating possible scenarios of evolution of our Universe, as predicted by Einstein’s theory of General Relativity or extension of it, using gravitational-wave observations from next-generation gravitational-wave observatories (either ground-based or space-based). After having familiarized with the basics of the theory of gravitational wave physics and Bayesian statistical inference, the student will get acquainted with some of the state-of-the-art techniques to do gravitational-wave cosmology. The student will acquire the skills (both theoretical and computational) to carry out the Bayesian parameter estimation of few cosmological models, focusing on gravitational-wave signals emitted by black hole and neutron star binaries.
  • TOPICS IN SIGNAL PROCESSING AND GRAVITATIONAL WAVE DATA ANALYSIS
    Gravitational waves emitted by the collision of black holes and neutron stars are now being detected by ground-based gravitational wave observatories. The use of sophisticated statistical signal processing techniques are paramount to extracting these weak gravitational wave signals that are engulfed in detector noise. With guidance, the student will investigate these statistical techniques with the overall goal of using Bayesian techniques to build a basic sampler to extract gravitational signals buried in detector noise.
  • GRAVITATIONAL WAVE EMISSION FROM TIDAL DISRUPTION EVENTS
    Tidal disruption events (TDEs) occur when a star, orbiting around a black hole (BH), is torn apart due to the BH tides. These events are very luminous electromagnetic sources, but they also emit gravitational waves (GWs) within the frequency range where future space-based detectors will work (LISA and Deci-Hertz observatories). This project aims to better comprehend this kind of system (or similar configurations). The student is expected to study selected papers regarding the theoretical aspects of flyby encounters between stars and BHs and then to use analytical and/or numerical methods to investigate the gravitational emission from these sources.

| Nuclear Physics

  • EXPLORING NUCLEAR MATTER UNDER EXTREME CONDITIONS WITH PARTICLE CORRELATIONS
    Heavy-ion collisions are the only terrestrial means to study the nuclear equation of state (EoS), namely the relation between density, temperature and pressure of nuclear matter under extreme conditions. These conditions play a key role in neutron stars and in phenomena like gravitational waves, supernovae explosions and stellar nucleosynthesis. During heavy-ion collisions studied at the Grand Accelerateur National d’Ions Lourds (GANIL), a large variety of particles are produced. They can be detected and correlations between their momentum vectors allow us to explore extreme density and temperature states through which the colliding system evolves. The student will be involved in developing correlation techniques between particles, via construction of algorithms to be used with large data sets, to observe the production of several resonances in particle-particle correlation spectra. These resonances correspond to the production of exotic nuclear species living for a very short time, of the order of 10-24-10-16 s, and reflecting the properties of matter under extreme conditions to be studied and linked to the equation of state and its impact on nuclear physics and astrophysics.
  • SIMULATING ENERGETIC NUCLEUS-NUCLEUS COLLISIONS
    Energetic collisions between two atomic nuclei produce systems under extreme conditions that evolve over a very short time, between 10-24 and 10-16 s, breaking-up into neutrons, protons and nuclear fragments. The time evolution of these explosive processes cannot be directly studied over those short time scales, even with the most advanced experimental techniques. Experimentally, we detect all the produced fragments, identifying them in mass and charge, and measuring their velocities. With this final state we need back-tracing the reaction to its original conditions, produced during the impact. This can be accomplished only with advanced nuclear many-body software simulation codes, where nucleons and protons evolve and collide under the combined effect of their mutual nuclear and Coulomb interactions. The student will be involved in using these codes, based on semiclassical approaches or on quantum molecular dynamics approaches, exploiting computing power and algorithms aimed at constructing observables to be compared to experimental results and help understanding the properties of nuclear matter under extreme conditions, relevant also in astrophysical phenomena such as nucleosynthesis and the properties of compact stars.

| Particle Physics