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</head><body style="zoom: 0%;"><div class="gmail_quote" >En 28 nov. 2022, en 15:59, David Rousseau <<a href="mailto:rousseau@ijclab.in2p3.fr" target="_blank">rousseau@ijclab.in2p3.fr</a>> escribió:<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<p><b id="docs-internal-guid-2a942c48-7fff-23cb-2055-bf3ec0393615" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"></b></p>
<p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b id="docs-internal-guid-2a942c48-7fff-23cb-2055-bf3ec0393615" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Hi, </span></b></p>
<b id="docs-internal-guid-2a942c48-7fff-23cb-2055-bf3ec0393615" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b id="docs-internal-guid-2a942c48-7fff-23cb-2055-bf3ec0393615" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Please find the PhD opening below. Thanks for forwarding it to potentially interested M2 students.</span></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Best regards, </span></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">David Rousseau</span></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">
</span></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">title : Fair Universe : uncertainty-aware Artificial Intelligence for ATLAS experiment Higgs boson Physics</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Application deadline 11 December 2022.</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">This 3 years Université Paris-Saclay PhD is funded through Fair Universe project, </span><a href="https://cs.lbl.gov/news-media/news/2022/new-fair-universe-project-aims-to-build-supercomputer-scale-ai-benchmarks-for-hep-and-beyond/" style="text-decoration: none;"><span style="font-size: 11pt; font-family: Arial; color: rgb(17, 85, 204); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;">https://cs.lbl.gov/news-media/news/2022/new-fair-universe-project-aims-to-build-supercomputer-scale-ai-benchmarks-for-he</span></a></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><a href="https://cs.lbl.gov/news-media/news/2022/new-fair-universe-project-aims-to-build-supercomputer-scale-ai-benchmarks-for-hep-and-beyond/" style="text-decoration: none;"><span style="font-size: 11pt; font-family: Arial; color: rgb(17, 85, 204); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;">p-and-beyond/</span></a><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;"> </span></b></p><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">The PhD will be co-supervised by David Rousseau (IJCLab, CNRS/IN2P3, ChaLearn) and Isabelle Guyon (Google Brain, UPSaclay/LISN, ChaLearn).</span></b></p><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">It is open to students expecting to obtain a Master 2 (or equivalent) in Particle Physics by summer 2023. It would typically start in Oct 2023 and possibly be preceded by an internship in late spring 2023. The successful candidate is expected to have an excellent track record in physics, but also to demonstrate interest in advanced Machine Learning algorithms.</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Physicists ultimately write papers with measurements which always include an assessment of uncertainties, including the impact of Nuisance Parameters (the parameterized unknowns) in systematic uncertainties. How to evaluate the uncertainties on a more and more complex model? How to build confidence in a complex ML model, and how to convince our peers about it? How to deal with the uncertainties on the input of the models to maximise the overall accuracy?</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">The Fair Universe project aims at releasing public datasets of increasing complexity and at developing strategies to evaluate uncertainties and reduce them with Machine Learning, in the context of particle physics. </span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">The PhD candidate will be a member of the ATLAS experiment. </span></b></p><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">In the first year, s/he will work at half-time on an ATLAS Qualification Task to be defined, and on the other half time on benchmarking different Machine Learning uncertainty mitigation techniques on public datasets developed by collaborators in Fair Universe project, starting from the techniques available in the literature (see bibliography). S/he will participate to the definition of public competitions on the theme.</span></b></p><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">From the second year on, s/he will develop an analysis of the measurement of Effective Field Theory parameters for the Higgs boson in the off-resonance Higgs to four lepton channel, using advanced Machine Learning algorithm. In particular, Simulation Based Inference (SBI) allows for fully exploiting the event by event information by estimating the likelihood ratio with a Neural Network; it has been demonstrated to be particularly efficient in this channel due to a quantum interference effect between the Higgs signal and the main background. The improved sensitivity allows unique constraints on several Effective Field Theory operators from LHC Run 3 dataset.</span></b></p><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Currently, the impact of Nuisance Parameters on the sensitivity is evaluated a posteriori. The techniques developed during the first year will be applied (and possibly complexified) on this channel, anticipating that different types of Nuisance Parameters might call for different strategies. </span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">David Rousseau is a particle physicist member of the ATLAS collaboration. After many years developing the ATLAS experiment software, he has been promoting the use of Machine Learning in High Energy Physics since 2014 with developments in particular concerning generator models or Simulation Based Inference. Within ChaLearn and with Isabelle Guyon he has organized the Higgs Boson Machine Learning challenge in 2014, which has played a major role in promoting Machine Learning to physicist and raise awarenesss about Machine Learning in the High Energy physics community. They have also organized the TrackML challenge to help the development of advanced algorithms for particle tracking at the LHC.</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Isabelle Guyon is director of research at Google Brain, in detachment from her position as professor of Artificial Intelligence at Université Paris-Saclay (Orsay). She specializes in data-centric AI, statistical data analysis, pattern recognition, and machine learning. Her areas of expertise include computer vision, bioinformatics, and power systems. Her recent interests include meta-learning and applications of machine learning to the discovery of causal relationships. Prior to joining Paris-Saclay she worked as an independent consultant and was a researcher at AT&T Bell Laboratories, where she pioneered applications of neural networks to pen computer interfaces (with collaborators including Yann LeCun and Yoshua Bengio) and co-invented with Bernhard Boser and Vladimir Vapnik Support Vector Machines. She is president of Chalearn, a non-profit dedicated to organizing challenges.</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">The PhD candidate will be based at IJCLab-Orsay, with frequent short stays at CERN and participation in relevant workshops and conferences. IJCLab is the largest particle physics laboratory in France, depending mainly on Université Paris-Saclay and CNRS/IN2P3. It is one of the founding laboratories of ATLAS (then with the name LAL) with major contributions to the Liquid Argon Calorimeter and to software, and more recently to the Inner Tracker and High Granularity Timing Detector, and with major contributions to Higgs boson physics.</span></b></p><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;">
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</b><p dir="ltr" style="line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;"><b style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-style: normal; font-variant-caps: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; text-decoration: none; font-weight: normal;"><span style="font-size: 11pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-weight: 400; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Interested candidates should provide a cover letter, CV and 2 letters of references. They should not hesitate to contact David Rousseau and/or Isabelle Guyon for details before submission, in particular if they are not already in the French system.</span></b></p><br class="Apple-interchange-newline">
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<pre class="moz-signature" cols="72">--
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David Rousseau, DR CNRS, <a class="moz-txt-link-abbreviated" href="mailto:david.rousseau@ijclab.in2p3.fr">david.rousseau@ijclab.in2p3.fr</a>
<a class="moz-txt-link-freetext" href="https://users.ijclab.in2p3.fr/david-rousseau/">https://users.ijclab.in2p3.fr/david-rousseau/</a>
IJCLab-Orsay, CNRS/IN2P3, Université Paris-Saclay, France
@ IJCLab : Bat 200 Pièce 142 : +33 (0)1 64 46 85 91
@ CERN : 40/1-D12 : +41 (22) 76 73857
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