Sort by
Refine Your Search
-
The Materials Science, Energy, and nano-engineering (MSN) is a department at Mohammed VI Polytechnic University that aims to makes use of innovative research and education in order to promote solution development
-
professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech. ABOUT MSN DEPARTMENT The Materials Science, Energy, and nano-engineering (MSN) is a department at
-
a highly motivated and skilled Postdoctoral Researcher to join a multidisciplinary team investigating the use of microporous materials for agricultural applications. The successful candidate will
-
aspires to make a lasting impact on national, continental, and global scales, positioning itself as a leader in education, research, and innovation. The Materials Science, Energy, and Nano-engineering (MSN
-
, positioning itself as a leader in education, research, and innovation. The Materials Science, Energy, and Nano-engineering (MSN) department at Mohammed VI Polytechnic University focuses on innovative research
-
staff position within a Research Infrastructure? No Offer Description POSTDOC POSITION IN ADVANCED COATING OF LFP MATERIALS – IN COLLABORATION WITH THE UNIVERSITY OF WATERLOO, CANADA We are seeking a
-
staff position within a Research Infrastructure? No Offer Description Job description: Sustainable Materials Research Center (SUSMAT-RC) is seeking a highly motivated and talented postdoctoral fellow to
-
, conversion and storage, and organic optoelectronics intelligent and advanced polymers and materials. Job Description The successful candidate will: Conduct original research of international excellence. Design
-
(2 positions) Job description: An exciting opportunity for a highly motivated and talented post-doctoral fellow (PDF) to work on a collaborative project between Sustainable Materials Research Center
-
SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models