-
this project, you will explore inverse data-driven and physics-based approaches and integrate multi-modal and multi-fidelity biomechanics tissue testing data to advance insights into the ex vivo and in vivo
-
available validated DEM simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data
-
to expand your (social) network. This position is a temporary assignment for 24 months. Selection process A pre-employment screening can be part of the selection procedure. Additional comments For more
-
promising solutions. This project aims to enhance SDB accuracy through deep learning pan-sharpening and physics-informed machine learning techniques. These methods will be tested in two regions worldwide and
-
13 Feb 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
-
13 Feb 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
-
, implementation & fabrication of infrared capable pixels using advanced silicon post-processing technology. Your key responsibilities include: Supporting the image sensor team with mask design, device physics
-
of angular estimation with sparse arrays, joint development of MIMO array topologies (sampling problem) and angular estimation algorithms (estimation problem) is required, while considering the physical
-
10 Apr 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
-
. Here, we focus on zero-defect manufacturing processes for resilient and adaptable data-driven additive manufacturing. We will work with CEAD who have developed an additive manufacturing process combined