Organisation : Faculté des Sciences, des Technologies et de Médecine (FSTM)
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            News
Engineering alumni on a visit at the University
En savoir plusOn 14 June 2019, five alumni from the class of 2006 in “Mechanical Engineering” came back to the University of Luxembourg. The visit was organised by Prof. Stefan Maas and Joël Da Cruz Antunes in order to connect former Uni.lu students with the current ones, in an informal atmosphere.
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            Events
Physics Colloquium: Rescuing the kinetic properties of coarse-grained simulation models
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            Events
Physics Seminar: Why one can never get bored of optics – investigations of soft materials with optical methods
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            Events
First PHYMS Workshop of the Physics and Materials Science Research Unit
En savoir plusThe first Workshop of the Physics and Materials Science Research Unit has the following goals:To increase awareness about the focus and research interests of each of the PHYMS groups.To foster unity within the Research Unit and encourage interdisciplinary collaborations.The talks will be given by various group members, who will introduce their group’s activities and fields of…
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Three students in science receive the “Top Student Prize”
En savoir plusDany Dos Santos Ramos, Laurence Lampecco and Julien Putz, respectively students in the Master en Sciences de l’Ingénieur – Efficacité Energétique et Economique (MEEE), Bachelor en Informatique (BINFO) and Master in Mathematics (MMATH), have recently been awarded the “Top Student Prize” by the University of Luxembourg for their excellent academic results.
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The BicsLab Partners Day: great success for the first edition
En savoir plusOn 13 May 2019, more than 50 attendees from the University of Luxembourg as well as Luxembourgish companies and institutions joined the “BicsLab Partners Day”: the scientific forum to meet and match BicsLab partners and Uni.lu students. This very first edition covered the specific theme: “ICT for a sustainable agriculture in Luxembourg”. The main objective…
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            Events
Physics Colloquium : Machine Learning Approaches for an Atomistic Understanding of Amorphous Functional Materials
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