Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- CNRS
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- The American University of Paris
- Université de Technologie de Belfort-Montbéliard
- Aix-Marseille Université
- Arts et Métiers Institute of Technology (ENSAM)
- BRGM
- CEA
- Consortium Virome@tlas
- Ecole Centrale de Lyon
- Ecole polytechnique
- FEMTO-ST institute
- French National Research Institute for Sustainable Development
- ICMMO
- INSERM U1183
- IRISA
- Institut Curie - Research Center
- Institut of Mathematics of Marseille
- Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique,
- Observatoire de la Côte d'Azur
- University of Paris-Saclay
- Université Côte d'Azur
- Université Grenoble Alpes
- Université Paris-Saclay (UPS)
- Université Paris-Saclay GS Mathématiques
- Université de Caen Normandie
- École Normale Supéireure
- École nationale des ponts et chaussées
- 20 more »
- « less
-
Field
-
Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
PhD supervisors and co-direction Name: GAUCI Surname: Marc-Olivier Grade: HDR Institution: ICARE, Inserm U1091 Email: gauci.mo@chu-nice.fr Phone number: 04 92 03 70 27 Name: Micicoi Surname
-
published openly in the form of process flowsheet databases. Skills: Machine Learning/Deep Learning skills are essential, as well as programming proficiency, as well as some knowledge of energy or process
-
Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country France Application Deadline 1 Nov 2025 - 12:00 (Europe/Paris) Type of Contract Permanent Job Status Full-time Offer Starting Date 1
-
in the area of scientific computing and Computational Fluid Dynamics. Prior Experience in turbulence modelling, machine learning or the Lattice Boltzmann method is an advantage. Operational skills
-
correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
-
experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
-
computational modeling and/or analysis of complex biological systems, integrating state of the art tools such as machine and deep learning approaches. Experience in managing biological databases and statistical
-
: • PhD in Geography (Remote Sensing, Geomatics), Computer Science, Agricultural Sciences • Skills and/or knowledge in artificial intelligence (Machine Learning) and programming: proficiency in Python
-
to candidates from a broad range of AI subfields, including, but not limited to machine learning, generative AI, computer vision, representation and reasoning, natural language processing
-
clinical research center is a plus; Knowledge and experience of machine learning methods; Constructive attitude, flexibility, outgoing and service oriented; Excellent communication, negociation and