11 algorithm-development-"https:" PhD positions at Delft University of Technology (TU Delft) in Netherlands
-
these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine
-
multidisciplinary project at the intersection of Robotics and wildlife conservation. The project aims to develop autonomous drones capable of perching on natural structures, inspired by the way birds rest on branches
-
solid foundation in numerical analysis, partial differential equations, and linear algebra. Theoretical and Practical Balance: You enjoy developing and analyzing mathematical theory, but also have the
-
to test and demonstrate the developed concepts and algorithms for integrated (re)planning. This PhD research will use a mixture of techniques from logistics, operations research, multiple-criteria decision
-
this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
-
water quality in cities is vital for a healthy city: in this PhD you will develop monitoring and modelling strategies to help design resilient water cities of the future. Job description Cities depend
-
transportation systems may include a fleet autonomous cars, vans, and buses. This PhD position within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of
-
expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
-
. While the chosen design has a significant effect on the most important aspects of users’ experience, the algorithms, and thus the supply decisions, are based on users’ preferences. This PhD position
-
the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from