Sort by
Refine Your Search
-
, particularly EEG; • Programming experience, particularly in R and Python; • Proficiency in statistical methods commonly used in psychology and neuroscience (ANOVA, linear models, etc.); • Familiarity with
-
resistance of ceramic shell moulds used in investment casting. Advanced in situ experiments combined with multi-scale Finite Element Method (FEM) modelling will be employed to identify the key stress and
-
to identify suitable MOFs and their synthesis conditions; • Synthesizing pre-selected MOFs using conventional methods (solvothermal, hydrothermal, or ambient-pressure synthesis); • Performing structural and
-
. - Applied Mathematics and Statistics: Knowledge of statistical methods and algorithms for data analysis, including model fitting, regression, and sensitivity analysis. Expertise - Scientific Collaboration
-
-temporal context and their environment. ECO-EVO BIODIV draws on a wide range of conceptual frameworks, approaches and methods from an interdisciplinary perspective. Within the framework of ECO-EVO BIODIV
-
settings with limited data and transfer learning across species from human to mouse, and beyond. • Apply explainability methods to extract biological insight from trained models. • Keep up to date with
-
these processes requires AI and bioinformatics methods able to integrate heterogeneous, high-dimensional data. The ShadowEV-GBM project brings together spatial omics, metabolomics/lipidomics, molecular profiling
-
, and component failures; • Ensure a high level of resilience to incidents affecting equipment, sensors, or communication infrastructure. However, traditional protection and monitoring methods
-
the organic synthesis of large aromatic ligands • Synthesize lanthanide and uranium complexes with organic ligands in an inert atmosphere • Characterize the complexes using routine methods such as X-ray
-
of steel compositions. The future potential of the model / numerical tool to replace costly trial- error method will also be evaluated. The Institute Jean Lamour (IJL) is a joint research unit of CNRS and