Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
-
remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
-
data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
-
on lncRNA structure. These experimental constraints will then be used to guide deep learning-assisted RNA 3D structure prediction tools, in order to generate ensembles of structural models. Clustering and
-
the SPIN Doctoral School (ed-spin.doctorat-bretagne.fr). Vincent Lebastard at IMT-Atl Nantes will co-supervised the PhD thesis. This thesis is part of the PEPR Acc Robotique MiniRo (https://anr.fr/fileadmin
-
to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR3228-SEVBOR-002/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
-
archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
-
to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8023-ANTSAI-004/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears
-
, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
-
, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements