Sort by
Refine Your Search
-
. Thus, please see the student information and admission criteria at https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-electrical-engineering . Desired background We are looking for
-
. A strong background in energy-system modelling, mathematical optimization, machine learning, reinforcement learning, or data-driven decision-making is appreciated. Experience with programming and
-
graph theory. Computational methods are central; the team operates a 500‑core cluster. We both compete with and leverage AI; see: https://www.aalto.fi/en/news/researcher-cracks-new-kissing-number-bounds
-
algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council of Finland project ELPH-ML ( https://research.fi/en/results
-
research experience in mechanics Prior exposure to numerical/computational modelling methods (e.g. discrete element method or finite element analysis) Strong programming skills Good written and verbal
-
programming, GPU programming) Astrophysical fluid dynamics and/or magnetohydrodynamics Radiative transfer in astrophysics Machine learning or data analysis for physical sciences Strong programming
-
: Extending full-spectrum non-gray models for gases to solid particles Experimental characterization of fuel particles using FTIR Mathematical model formulation and programming Model implementation in
-
doctoral studies at Aalto University School of Electrical Engineering. Thus, please see the student information and admission criteria at https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in
-
phenomena and development of biobased barriers, foams, and emulsions Advanced textile recycling, including flotation‑based methods Learn more: https://www.aalto.fi/en/department-of-bioproducts-and
-
whole fleet can act as one Virtual Power Plant. Read more about the project and other participants here: https://aegis-dn.eu/ Your role: You will be working on “End-to-End Energy Modeling for