Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Sciences (FHSE) at the University of Luxembourg brings together expertise from the humanities, linguistics, cognitive sciences, social and educational sciences. People from across 20 disciplines are working
-
interdisciplinary research and computational biology in particular. The fellow will join my team at IPhT, in Paris-Saclay. The IPhT is located just outside of Paris in picturesque Gif-sur-Yvette at the French CEA and
-
together world-class researchers from various fields, including neurophysiology, computational neuroscience, auditory cognition, genetics and genomics, cell biology and gene therapy. It is located in
-
of partners, putting the collective interest first. You have demonstrated your ability to manage a research program with the necessary scientific rigor. Your enthusiasm for innovation will enable you
-
, Statistics, Epidemiology or related disciplines Experience in handling longitudinal and birth-cohort datasets Extensive experience in quantitative research (Stata, R, Python, etc.) Fluent in English (speaking
-
Sciences (FHSE) at the University of Luxembourg brings together expertise from the humanities, linguistics, cognitive sciences, social and educational sciences. People from across 20 disciplines are working
-
with mouse models of infection will be appreciated. We are looking for strongly motivated and highly collaborative candidates having good communication skills in English and a sense of team spirit
-
spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
-
, particularly in the context of wave equations. Proficiency in numerical implementation and computational methods will be appreciated. Candidates with a PhD in semiclassical analysis who are keenly interested in
-
technology is reducing the write current, which is intrinsically linked to the charge-to-spin current conversion ratio (), a key parameter defining the efficiency of SOT materials. The TopMemo project aims