Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Doctoral Researcher in Power System Dynamics Employer AALTO UNIVERSITY Location Finland (FI) Salary 3143 €/month Closing date 18 Oct 2026 View more categories View less categories Job Type Research
-
-electrical-engineering . Desired background We are especially looking for candidates with a strong background in one or more of the following areas: Experience with power system simulation tools
-
is one of the six schools of Aalto University. Our portfolio covers fields from natural sciences to engineering and information sciences. In parallel with basic research, we develop ideas and
-
, computational science, or closely related). Relevant coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed
-
coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
-
communications, statistical signal processing, and software-defined radio experimentation . Depending on your background and interests, your research may emphasize theoretical modelling and algorithms
-
communications, statistical signal processing, and software-defined radio experimentation . Depending on your background and interests, your research may emphasize theoretical modelling and algorithms
-
realistic downstream processing. Your role and goals As the Doctoral Researcher, you will take primary responsibility for detecting generated audio content from multiple sources , and work jointly
-
authenticity of generated and watermarked audio data, improving content-based audio watermarking, and evaluating robustness against removal, spoofing, adversarial attacks, and realistic downstream processing
-
foliage components, and water-content-related properties needed for microwave VOD modelling. The work will include processing existing TLS datasets and collecting new field data from contrasting ecosystems