Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
into applications in close collaboration with industrial partners worldwide. You can read more about the department at www.es.aau.dk. Your work tasks Modern wind turbine testing and verification face a series of data
-
of student projects and participation in courses related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the
-
contexts, or a strong motivation to explore how different groups of learners appropriate AI-based tools. A strong technical background, ideally in computer science, software engineering, human-computer
-
, software, and High Performance Computation (HPC) infrastructure; • Excellent scientific infrastructure; • Participation in project meetings and international conferences; • Flexible working hours
-
-and-egg" problem of sampling: developing algorithms that learn to bias simulations automatically without requiring prior knowledge of the mechanism. You will contribute to open-source software
-
Information Modeling (BIM) and energy modeling software. Data Science Proficiency: Knowledge of data modeling, ontologies (RDF/OWL), or semantic web technologies is highly desirable. Programming: Strong
-
software development, including version control, testing, and reproducible research workflows; familiarity with CI/CD practices is an advantage. Experience with supervision of BSc and MSc student projects
-
. Experience working with deep learning software stacks, extensive software development experience, and knowledge of machine learning frameworks (such as transformers, torch, Megatron, triton etc.) are pluses
-
project is in close collaboration with the Head of Software - Technology and Innovation at EBU. You will have an extended and paid stay in Geneva with the EBU. As part of RePIM you will participate in
-
fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind