116 parallel-processing-"International-PhD-Programme-(IPP)-Mainz" Postdoctoral positions at CNRS
Sort by
Refine Your Search
-
Additional Information Eligibility criteria ● A relevant PhD degree in semiconductor physics, material sciences, or similar. ● Hands-on experience with III-V semiconductor deposition processes (e.g. MOCVD, MBE
-
Description The researcher will be responsible for developing and implementing a protocol aimed at studying motion processing and perception in both patients with macular degeneration and control participants
-
mathematics. The skills expected for the position are: - excellent command of the theory of random processes, in particular measure-valued Markov processes; - good general knowledge of population dynamics
-
innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
-
Description The researcher will use modeled surface ocean microplastic abundances and improved sea-spray-based emission functions to represent ocean–atmosphere transfer processes. Using the GEOS-Chem global
-
on estimated movements using eDCCs. The research will focus on data simulated using the Monte Carlo method and real data from clinical SPECT scanners with a parallel collimator, such as those available at LUMEN
-
functionalities to enable these features. In parallel of this work, the retained physicist will be able to start or continue researches on different science topics, for galactic or extragalactic objects
-
of scientific activities (1 conference, 1 research school, 1 or 2 workshops, 2 paired research projects + any other parallel activities such as Masterclasses, FRUMAM conferences, etc.). It is organized
-
identify the morphogenetic processes underlying skeletal muscle growth and regeneration. Oversee and conducting innovative pipelines. As part of this research project, you will be required to: - Develop and
-
of an effective system for rapid and robust storage and optimised processing of large quantities of collected data. 2. Development and improvement of algorithms for processing acquired geophysical data in order to