Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
-
SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
Temporary contract | 24 months | Belval Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
-
after damage. Methodologically, the project aims to develop novel organoid-on-a-chip models of kidney injury. The applied techniques will include mouse and human kidney organoids, tissue engineering
-
undergraduate teaching departments: biotechnology, bioengineering, bioinformatics and plant science and technology. 1 comprehensive experimental center and 5 research institutes. There is a biology postdoctoral
-
, like rituximab, can be effectively boosted by vaccination while others cannot (Gröning et al, Front Imm 2023). You will use recently developed technology in genomic and proteomic B cell / antibody
-
(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
-
Temporary contract | 24 months | Belval Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
-
PhD Degree in a relevant scientific field (e.g. computer science, data science, mathematics, engineering, or related); Strong understanding of generative models (e.g., VAEs, GANs, transformer-based
-
you will report research results in high-impact scientific journals. Your profile We are searching for a highly motivated candidate who has A PhD in agricultural science, agricultural engineering
-
skills and curiosity about complex systems. Position Overview You will design and implement new computational and statistical models to reverse-engineer causal networks from noisy, high-dimensional, multi