13 machine-learning-phd Postdoctoral positions at CNRS

Post-doc position on AI-augmented boundary plasma modelling for turbulent transport simulations in WEST and ITER tokamak (M/F)

physics or computer science, with a solid background in AI/machine learning techniques. A background in plasma transport phenomena as well as an experience with data analysis, statistical methods, and

Postdoctoral Researcher Position in Quantum Neuromorphic Computing with Superconducting Circuits(M/F)

. Fujii, K. & Nakajima, K. Harnessing disordered-ensemble quantum dynamics for machine learning. Phys Rev Appl 8, 024030 (2017). 2. Rudolph, M. S. et al, Generation of High-Resolution Handwritten Digits

Post-doctoral researcher or researcher in sea ice/ocean/atmosphere modeling and prediction (M/F)

or oceanography. Research background should demonstrate competence -- or at least a clear and strong interest -- in artificial intelligence and machine learning to be applied in the field of environmental sciences

Postdoc in materials science (experimental study and DFT calculation) (M/F)

or as materials for transportation. Intensive calculations within the framework of density functional theory (DFT) will provide the basis for building machine-learning models to explore the range

Postdoctoral position on ATLAS (M/F)

into subtle effects in diboson channels and is expected to co-supervise a PhD student studying polarisation effects in diboson events, using machine learning techniques. The group has expertise in data

Postdoc (M/F) in Physics-Informed Machine Learning for EEG neuroscience data

academic knowledge of the field, evidenced by a PhD thesis in computer science, physics or computational biology/neuroscience - good programming skills in Python, development and evaluation of machine

Researcher specialized in electrode materials and battery cells M/F

the relationships between manufacturing parameters and battery cell performance. The collected data and the unraveled insights will be used to calibrate and validate pioneering physical and machine learning models

Post-doctoral researcher (M/F) on generative model applied to calorimeter simulationodèle génératif appliqué à la simulation calorimétrique

simulation or machine learning. Experience with HEP simulation with generative models would be a plus. Applicants must also demonstrate teamwork skills and an ability to fit in a multidisciplinary scientific

Post-Doctoral Researcher (M/F) in Medical Image Processing and Artificial Intelligence

innovative methods for processing and analyzing MRI images (3 Tesla and 7 Tesla) of various modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. The aim is

Post-doctoral position for the study of zooplankton traits from imaging data (M/F)

traits, possibly through machine learning, and thus explore the functioning of pelagic ecosystems at a finer level than just community composition. Within the TraitZoo consortium, it will also be possible