Sort by
Refine Your Search
-
the models developed and identify the main technical obstacles to be overcome for future industrial implementation. 7. Improvement of the internal code for simulating thermodynamic cycles. The existing
-
). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines
-
: proficiency in Monte Carlo simulation codes, such as GEANT 4 or PENELOPE. Bayesian statistics. • Laser polarisation system: appetite for experimental physics, experience with lasers not required but would be a
-
. - Experience in coding (python or other computer language). - Proven track record of publications in peer-reviewed journals. - English (written/oral) level of at least B2 (according to the common European
-
- evolutionary theories ● Interpretation and formatting of the results obtained (publications) ● Proficiency in programming languages (Bash, Python, R), code management tools and software environments (Gitlab
-
formation. For reasons of computing time, the detailed mechanisms that describe this complex chemistry must be reduced before being used in CFD codes (Fiorina et al., 2015). An interesting method is the
-
refrigerator (CNDR), which would allow ultra-low temperature researchers to take full advantage of cryogen-free technology. - Based on the existing codes, propose a route for a software versatile enough to model
-
candidate will use the 'Phase_Field' code developed within the GPM UMR 6634 modeling team. - Writing of scientific publications. GPM (Materials Physics Group, UMR CNRS 6634) is organized in 5 departments
-
-dependent approaches. -Proficiency in high-performance computing (MPI/OpenMP/GPU) and scientific code development is a plus. -Interest in attoscience and/or matter–antimatter physics is an asset. -Ability
-
. Activities: Development of mathematical models. Development of probabilistic inference algorithms. Code implementation, with a particular focus in Julia. Method validation. Application of models on curated