Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
21 Mar 2026 Job Information Organisation/Company University of Basel Research Field Biological sciences » Other Computer science » Other Medical sciences » Other Researcher Profile Recognised
-
Research Framework Programme? Not funded by a EU programme Reference Number 5501-26831 Is the Job related to staff position within a Research Infrastructure? No Offer Description The Paul Scherrer Institute
-
datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
-
years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems
-
the BedrettoLab, evaluation of seismic sensors (e.g., different types of seismometers as well as distributed acoustic sensing technology) Design and Installation of a Multi-Sensor Monitoring Network in the Hondrich
-
The power system is changing, largely driven by the energy transition and climate change. The large shares of renewables, both centralized and distributed, are posing new challenges to system
-
, particularly with respect to fouling and moisture distribution. Understanding these parameters is essential for predicting long-term track performance and planning maintenance interventions. Project background
-
CS Practical knowledge of RL and IL (e.g., behavioral cloning, inverse RL, dealing with distribution shifts) with applications in (industrial) robotics Hands-on experience with robotics or other
-
component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
-
during field measurements, capture high-resolution imagery of cloud droplets and ice crystals to determine their size distributions and types. The resulting large datasets (often several terabytes