Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
enzymes and can be engineered to generate reactive oxygen species (ROS) locally and in a controlled manner. The position is within the Marie Skłodowska-Curie Doctoral Network Implant-to-Market (i2M
-
- and private-sector partners to develop knowledge and competence for resilient and diversified forest landscapes. The doctoral student will become part of this active network and the department’s forest
-
diversified forest landscapes. The doctoral student will become part of this active network and the department’s silviculture research environment. Read more about staff benefits and life as an SLU employee
-
of neural networks, for reconstructing MR images directly from MR signals. By incorporating a physical model of the MR signal into the training of the INR network, we aim to compensate for the effects
-
. This project investigates how such patterns can be designed systematically to make communication timing difficult for an external observer to predict, while maintaining closed-loop stability and using network
-
opportunity to gain experience in teaching and supervision. You will become a member of the Network of Young Scientists (NYS) within CH2ESS, which organizes workshops, field excursions, interdisciplinary
-
competence for resilient and diversified forest landscapes. The doctoral student will become part of this active network and the department’s forest pathology research environment. Read more about staff
-
to investigate the potential of using Implicit Neural Representation (INR), a class of neural networks, for reconstructing MR images directly from MR signals. By incorporating a physical model of the
-
project takes a different perspective. It starts from the idea that social networks can be supportive and, at the same time, generate social deficits: pressures, stigma, and misinformation (Offer 2021
-
at the intersection of AI, deep learning, computational neuroscience, and vision science. You'll develop biologically realistic neural networks to understand how individual differences in the brain shape perception