Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
animal models and knowledge of interactions between diet, intestinal microbiota and health. Experience with microbiology and gut microbiome analysis is a plus, but not a requirement. Required skills
-
directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
-
background in preferably more than one of the following areas: Thermodynamic analysis and simulation of energy technologies/processes/systems Programming tools such as Python, Matlab, Modelica, Pytorch, etc
-
for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
-
“Bioactives – Analysis and Application”. As part of this prestigious Alliance PhD program, you will collaborate closely with Queensland University in Australia and the University of Copenhagen in Denmark
-
offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
-
PostDoc in the project). Collaborating with fellow researchers across the UPLIFT network, including those focused on digital twins at DTU Chemical Engineering- As a PhD candidate, your work will adapt
-
techniques in enzyme kinetics and structure-function analysis Contribute to pioneering research in the green transition and circular economy Be part of a vibrant international research community with excellent
-
algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
-
powerful ideas and tools at the intersection of topological band theory, symmetry analysis, and photonics. You will work on developing and applying these ideas to discover new topological phenomena, design