Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
programming languages and programming abstractions, including LLM-assisted quantum programming * Quantum intermediate representations * Quantum compilation, including AI/ML-assisted compilation
-
programming languages and programming abstractions, including LLM-assisted quantum programming * Quantum intermediate representations * Quantum compilation, including AI/ML-assisted compilation
-
Security”. The postdocs will conduct research on program analysis within the Programming Languages, Logic, and Software Security research group at Aarhus University. The focus of the positions will be in
-
visual perception. Good programming (Python) skills are required along with a good understanding of empirical methods and ways to connect empirical findings with model behavior. The position also
-
programming languages and evaluated on both real-world bugs and code modified by AI coding assistants. The broader aim is to determine when code contains enough information to support its own repair and when
-
programming, preferably dynamic web-programming demonstrate proven scientific excellence be able to work both independently and collaboratively while contributing creatively in refining project
-
experience and capability in handling quantitative data and programming. If you already have used data-driven computational methods to model cognitive or behavioural change in any substantive domain, that
-
science, geoscience, physics, engineering or a related discipline. Experience with quantitative data analysis and scientific programming, preferably in Python is required. Experience with
-
: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling complex RL pipelines or custom simulation environments. Clean public
-
-stationary environments. Implementation Expertise: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling deep generative