-
criteria Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection Modeling & Simulation Experience: Familiarity with Building
-
, programmable OpenFlow/P4 switches and AI‑Boxes for fast inference, together with NetFPGA/DAG hardware for sub‑millisecond failure detection and a Timeseries‑DB/Grafana monitoring platform for closed‑loop testing
-
inference, counterfactual explanations, or uncertainty quantification in deep learning Evidence of high quality scientific writing, publications, a strong master's thesis, research software, or relevant open
-
vessel as it is, but support AI-assisted inference: surfacing what else is affected by a change, what may be missing from an incomplete design, or what the likely consequences are elsewhere in the vessel
-
and track defects in wheels, brakes, pantographs and other components. The PhD candidate will link TrainGate detections and early warnings with maintenance, incident, operational and cost data and
-
inspection portals to monitor passing trains at operating speed. Images, acoustic and vibration signals, and identification data are combined to detect and track defects in wheels, brakes, pantographs and
-
distances from the spatial structure of genetic genealogies across the genome, and the genetic relatedness among individuals; or develop and use biophysical models (hydrodynamics + particle tracking
-
critical infrastructure. Counter-drone systems must monitor the airspace as an integral part of a multi-layered air defense system, with functionality for detection, tracking and mitigating drone threats