Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, Algorithms, and Data" team at L2IT. Application procedure: Interested candidates must send: 1. A cover letter presenting their research project and their interest in joining the group 2. A Curriculum Vitae 3
-
data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
-
1 Aug 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique théorique et hautes énergies Research Field Computer science Mathematics » Algorithms Researcher Profile
-
24 Jun 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique théorique Research Field Computer science Mathematics » Algorithms Researcher Profile Recognised Researcher
-
aerosol properties from satellite observations using advanced inversion algorithms (such as the GRASP retrieval framework: https://www.grasp-earth.com/ ). Website for additional job details https
-
16 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire lorrain de recherche en informatique et ses applications Research Field Computer science Mathematics » Algorithms
-
, data, observations from physical, physiological and cognitive systems. They focus on the design of methodologies and algorithms for processing and extracting information, decisions, actions and
-
and cognitive systems. They focus on the design of methodologies and algorithms for processing and extracting information, decisions, actions and communications that are viable, efficient and compatible
-
telescopes. A major objective will be the development of an iMz-based XAO instrument for the Gran Telescopio Canarias (GTC), including the integration of new calibration approaches and control algorithms
-
methodological developments along the chosen direction (inference, active-matter theory, or machine learning). ◦ Algorithmic implementation and validation of the developed tools. 5. Validation on model systems