74 assistant-professor-computer-science-and-data-"Meta" PhD positions at Technical University of Denmark
Sort by
Refine Your Search
-
. These are essential components for optical quantum computers and quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between
-
. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Prof
-
manufacturing platforms, data engineering, and AI-powered maintenance solutions—key capabilities for driving efficiency in the competitive semiconductor industry and beyond. You will explore how operational
-
) therapy on the biology of γδ T cells and how can we use this knowledge to help us predict the success of therapy and prevent the development of side-effects. Position 1 will focus on the cellular and
-
, including EMODnet, trawl and dredge surveys, commercial catch and bycatch records, coastal vegetation data, citizen science catch rates, and environmental datasets from Copernicus. This will require working
-
deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
-
group and are expected to contribute to other departmental tasks. We expect that you have a background in biology or veterinary medicine and have an interest in interactions between diet, intestinal
-
candidate will be enrolled in one of the general degree programs at DTU. For information about our enrolment requirements and the general planning of the PhD study program, please see DTU's rules for the PhD
-
. Completing courses and training required for being awarded the PhD degree. Design and perform strain engineering works in Bacillus. Perform OMICS data analysis, especially RNAseq analysis. Specific
-
. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics