Organisation/Company: CNRS
Department: Laboratoire Univers et Théories
Research Field: Physics
Researcher Profile: Recognised Researcher (R2)
Country: France
Application Deadline: 26 Nov 2024 - 23:59 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 35
Offer Starting Date: 1 Jan 2025
Is the job funded through the EU Research Framework Programme? Horizon 2020
Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Gammapy is an open Python library for astrophysical very-high-energy (VHE) gamma-ray data analysis. Amongst its features, it enables joint fits of heterogeneous data sets, e.g., from different event types, from different gamma-ray instruments. Some work has also demonstrated that multi-wavelength (from optical to ultra-high-energy photons) or multi-messenger (gamma-ray and neutrino) analyses are possible with Gammapy.
The main objective of this position is to set up the Gammapy ability to jointly analyse VHE gamma rays and neutrinos. The retained candidate will implement support for VHE neutrino Instrument Response Files (IRFs) in the Gammapy library. She/he will also develop tools to support proper neutrino analysis methods in Gammapy, particularly unbinned forward folding techniques.
The addition of these features will enable research on different topics, e.g., studies of transient phenomena in the low count regime, joint gamma/neutrino studies of VHE data. The required person will achieve these research studies within the H.E.S.S., CTAO or KM3NeT collaboration.
Responsibilities
Gammapy developer (code, test, benchmark, documentation)
Participation in the Gammapy user support
Science analysis of data from the H.E.S.S. experiment or/and the KM3NeT telescopes
Gammapy is an open research library developed by a consortium of French, German, Spanish and Italian developers. It will be the main library for the Science Analysis Tool (SAT) of the CTA observatory (CTAO), which will be distributed freely. The APC and LUTh teams are heavily involved in the Gammapy project since its inception and have major responsibilities within the project (Lead Developer and Project Manager in APC).
Some members of the project's team are strongly involved in the H.E.S.S. experiment (responsible for an analysis chain that produces high-level H.E.S.S. FITS data) and heavily involved for CTAO, both on the scientific side (AGN, redshift, PSR/PWN, SNR, galactic center, PeVatrons) and on the software side (data model, science analysis tool, proposal handling tools, science data challenge, science platform, data dissemination). Some other members are strongly involved in the KM3NeT observatory (data analysis for neutrino oscillation and astrophysical studies, searches for core-collapse supernovae, for neutrinos from the galactic plane, and for neutrinos in coincidence with blazars and gravitational wave sources). The recruited candidate will then work closely with this team, and within the APC "High Energy Astrophysics" theme group (Integral, SVOM, Athena, H.E.S.S., CTAO, KM3NeT, Jem-EUSO, theory) and the LUTH gamma-ray group.
This position is funded by the European project ACME (Astrophysics Centre for Multimessenger studies in Europe, HORIZON-INFRA-2023-SERV-01). It involves 40 partners from 15 countries, over 30 research infrastructures (observatories and detectors, cyberinfrastructures and expertise centers) from Astronomy and Astroparticle domains, covering GW, Gamma & X-rays, neutrinos, CR, radio, optical. Within this project, Gammapy will be improved to enable multi-messenger data analysis workflows.
Knowledge
Very good knowledge in Python
Good knowledge in statistics
Expertise in VHE high-level analysis
Knowledge in VHE gamma-ray and neutrino detectors
Proficiency in English (written and oral)
Know-how
Experience in the design and development of complex software within an international organisation
Very good knowledge in Unix (Mac OS or Linux)
Experience with collaborative development software and platforms (e.g., git, GitHub)
Experience with the scientific python ecosystem
Some experience in code optimisation (time and memory) appreciated
Expertise in the statistical techniques of forward-folding
Knowledge in the VHE Instrument Response Files is very appreciated
Knowledge in Gammapy is highly encouraged
Personal Skills
Autonomy
Team spirit
Commitment and responsibility
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