Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 2 months ago
, Arts et Métiers and CNAM, dedicated to innovation in the fields of mechanical engineering, materials science and advanced numerical simulation. Located in the heart of the 13th arrondissement of Paris
-
, significantly enhancing the visibility of products, resources, materials, and activities. The PhD candidate will develop methods and processes that utilize such technologies to plan and coordinate manufacturing
-
researchers with different specializations, gain skills in computational technologies, and interact with world-class collaborators and industrial partners. Profile Recently obtained master degree in engineering
-
numerical modelling skills (e.g. Python, MATLAB, CFD codes) Personal characteristics Flexible and dependable Collaborative and independent Innovative and open minded Strong analytical skills Emphasis will be
-
will be involved in various international initiatives and engaged with different stakeholders. The candidate is expected to primarily but not exclusively deploy qualitative IS methods, with specific
-
sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
-
in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
-
and Topology; Analysis; Geometry; Numerical Analysis and Optimization; Probability and Statistics). (c) Production and edition of scientific papers and progress reports on his/her research work. (d
-
specific focus on cost-effectiveness, emission reduction, and social acceptability. The candidate will be involved in various (inter-)national initiatives and engaged with different political decision makers
-
efforts to contribute to safer marine operations, we actively explore possibilities to utilize both numerical and machine learning methods to enhance the accuracy and resolution of metocean forecasts. About