Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
is set to begin on July 1st, 2025, with flexibility regarding the start date. Profile We are looking for candidates with the following qualifications: A master’s degree preferably in Computer Science
-
the SVT course programme Contributing to the operation of the group and the Institute Profile You ideally have a Master’s degree in computer science, artificial intelligence, transportation engineering, or
-
Location: Sofia, Sofia 1784, Switzerland [map ] Subject Areas: Computer Science / All areas Quantum Computing / Quantum Computing Artificial Intelligence Machine Learning / Machine Learning Natural Language
-
Computer Science, Artificial Intelligence, or related field. Proven experience in machine learning and neural network architectures. Strong programming skills in Python and familiarity with PyTorch. Experience with
-
Contract length : 2 years, renewable twice, max. 6 years Rate : 100% The Department of Computational Biology (DBC ) is internationally renowned for its excellence in research pertaining to the analysis
-
. Profile You hold a Master's degree in a relevant field such as data science, computer science, physics, computational biology, or biomedical research. You are proficient in Python programming, with
-
Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by
-
informatics in rehabilitation, particularly in the development and implementation of digital solutions to support patient care, is advantageous, as is the ability to directly link scientific findings with
-
the “Basisprüfung” or its equivalent with good grades. MSc students and BSc students in the fifth semester or higher are preferred, although students earlier in their program will be considered if their grades
-
Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by