51 assistant-and-professor-and-computer-and-science-and-data PhD positions in Luxembourg
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
A PhD position is available at the Chair for ‘Urban Water Management’ (Prof. Dr. Joachim Hansen), Department of Engineering. The successful candidate will be hired in the frame of the PreWaPharm
-
We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
-
promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract
-
), immunofluorescence and microscopy Prior experience in RNA biology, NGS and/or Metabolism is an asset Understanding of common bioinformatics approaches and experience with one of the main programming languages for data
-
a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens
-
doctoral dissertation in Computer Science Assist in teaching activities and help in co-supervising Master and/or Bachelor students Contact: Prof. Dr. Christoph Schommer (Christoph.Schommer@uni.lu ) and/or Dr
-
applications and security of LLMs. For further information, please contact us at jerome.francois@uni.lu and lama.sleem@uni.lu
-
the advancements brought by AI, there is currently no tool sufficiently intelligent to fully aggregate and utilize diverse data sources to create a comprehensive and adaptive dashboard for taking
-
Qualification: The candidate should possess a MSc. Degree or equivalent in Engineering, Computer Science, or related fields. Experience: The ideal candidate should have some knowledge and experience
-
photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen