<html><head></head><body style="zoom: 0%;"><div class="gmail_quote" >En 20 dic. 2022, en 0:39, Pietro Vischia <<a href="mailto:pietro.vischia@gmail.com" target="_blank">pietro.vischia@gmail.com</a>> escribió:<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div dir="ltr"><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">Dear all,</span></div><div><br></div><div>please find below [1] some information on a PhD funding opportunity for applying machine learning techniques to HH->bbtautau studies with CMS data.</div><div><br></div><div>Thank you very much in advance for forwarding this to interested potential candidates in your institution!</div><div><br></div><div>Cheers,</div><div>Pietro<br></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">[1] Interested prospective students can examine the terms of the call and the thesis proposals by registering at: <a href="https://idpasc.lip.pt/pt_cern_grants/phd_programme/call" rel="noopener noreferrer" id="m_4096035225169720036m_141535180082483015gmail-LPNoLPOWALinkPreview_1" target="_blank">https://idpasc.lip.pt/pt_cern_grants/phd_programme/call</a><br aria-hidden="true"></span></div><div></div><br aria-hidden="true"><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">I would like to bring to attention the proposal #240, co-supervised by myself (<a href="https://idpasc.lip.pt/pt_cern_grants/phd_programme/call/18/thesis_proposals/240" rel="noopener noreferrer" id="m_4096035225169720036m_141535180082483015gmail-LPNoLPOWALinkPreview" target="_blank">https://idpasc.lip.pt/pt_cern_grants/phd_programme/call/18/thesis_proposals/240</a>
link accessible upon registration, but please find the details below
[1]), on HH->tautaubb with CMS data and advanced ML techniques: I
would appreciate it a lot if you could bring this to the attention of
interested candidates!</span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><b>The application deadline is 27<sup>th</sup> January 2023, 17:00 (Lisbon time).</b><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">Interested candidates are warmly invited to get in touch with me (the earlier the better) at <a href="mailto:pietro.vischia@cern.ch" target="_blank">pietro.vischia@cern.ch</a> <span style="font-size:12pt;background-color:rgb(255,255,255)">for any inquiry.</span><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">Cheers,</span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">Pietro</span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)">[1] Title: Machine Learning and Measurements of Higgs boson properties<br aria-hidden="true"></span></div><div><span style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"><ul><li><div><div><span>Workplan: </span></div><div><p>The
subject of this thesis is the search for double Higgs production,
decaying into taus and b-jets, at the Large Hadron Collider (LHC). The
work plan includes the study of the double Higgs production, each
subsequently decaying to pairs of taus and b-jets. Advanced Machine
Learning (ML) techniques will be used in the separation of signal and
background events. Searches for new physics in this channel can be
significantly improved with the additional data, and with improved
analysis techniques. </p></div></div></li><li><div><div><span>Summary: </span></div><div><p>The
discovery of the Higgs boson in 2012 was a major step towards improving
the understanding of the mechanism of electroweak symmetry breaking
(EWSB). With the value of the mass of the H boson now experimentally
measured, the structure of the Higgs scalar field potential and the
intensity of the Higgs boson self-couplings are precisely predicted in
the SM. There are, however, compelling reasons to believe the SM is not
complete. In particular, the LIP/CMS group is engaged in the study of SM
and BSM processes to fully exploit the opportunities of the
unparalleled energy of the LHC collisions. While measured properties are
so far consistent with the expectation from the SM predictions,
measuring the Higgs boson self-couplings provides an independent test of
the SM and allows a direct measurements of the scalar sector
properties. The self-coupling of the Higgs boson can be extracted from
the measurement of the Higgs boson pair production cross section. A
large amount of data of approximately 150/fb have been collected in
Run1+Run2 and are available to study this process. With the upcoming
Run3, additional 300/fb of data may become available in the next few
years and there will be excellent opportunities for major discoveries in
this domain. </p></div></div></li><li><div><div><span>Description: </span></div><div><p>The
main goal of the research program is to analyze the data and search for
the production of Higgs boson pairs via gluon-gluon and vector boson
fusion processes in final states with two bottom quarks and two tau
leptons. The use of Advanced Analysis tools, such as Machine Learning
and Deep Neural Network, will be pursued to enhance the sensitivity of
the study. With the large data samples collected in Run2 and those
expected to be collected in Run3 and beyond, the tools will be used to
better understand the data and extend the sensitivity to Higgs searches
to regions so far unexplored. The research will be carried out in the
context of the Portuguese participation in the CMS experiment at the
LHC, in the framework of the activities of one of the outstanding
research groups in High-Energy Physics in Portugal. Citing the Report of
the recent Institutional Evaluation performed by an international
review panel nominated by FCT: “The LIP-CMS group, while small in size,
is really outstanding and world-class”. The candidate is expected to
work in a team with a group of researchers. A strong motivation and a
keen curiosity are essential requirements. </p></div></div></li></ul></span></div><font color="#888888"><font color="#888888"><br clear="all"></font><br clear="all"></font><br clear="all"></div></blockquote></div></body></html>