Study of jet properties with the STAR experiment at RHIC
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- CTU, Prague
- Europe
- hep-ex
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- PostDoc
- Experiments:
Deadline on Apr 30, 2025
Job description:
Position is offered via CROP Postdoctoral Fellowship Programme at the Czech Technical University. The details of the programme and application procedure can be found at https://international.cvut.cz/jobs-at-ctu/crop-postdoctoral-fellowship-programme/
Eligibility criteria
The position is offered for 18 months, with the possibility of a 4-month secondment at Yale University. Candidate should have a Ph.D. degree at the moment of application, maximum of 8 years experience in research, from the date of the award of their PhD degree and must not have resided or carried out their main activity in the Czech Republic for more than 12 months in the 3 years prior to the Calls’ deadline.
Benefits and Conditions
Gross monthly salary of 83 531 CzK/month*
Family allowance 9044 CZK/month (for applicants with dependent family members)
Travel support for conferences and secondments
Topic of research:
Jets, collimated sprays of particles, are considered as an ideal tool for studies of the theory of strong interaction (quantum chromodynamics, QCD) in proton-proton collisions at high energies accessible at the largest colliders in the world, RHIC at BNL and LHC at CERN. Moreover, in heavy-ion collisions, jets serve as a valuable probe of the quark-gluon plasma (QGP), a new state of matter in which basic building blocks of matter, quarks and gluons are deconfined and resemble the state of our Universe in the first moments after the Big Bang. High statistics data collected by the STAR experiment at RHIC in combination with new analysis techniques allow to study jets including also their sub-structure and bring thus new, more detailed information about QCD and QGP properties. The project is focused on the experimental task of jet reconstruction and its direct application to the STAR data along with performing various Monte Carlo simulations and applying advanced analysis techniques (multidimensional unfolding, machine learning).
Contact:
- Jana Bielcikova (jana.bielcikova@fjfi.cvut.cz)
Posted 9 days ago, updated 9 days ago