Sort by
Refine Your Search
-
The Leadership and Management section at the Amsterdam Business School of the University of Amsterdam (UvA) invites applications for a PhD position. We are looking for a PhD candidate interested in
-
quality critical distributed data-centric computing systems with a specific focus on AI and machine learning-based approaches, research, develop, and validate scheduling, optimization, and adaptation
-
programming (e.g., R, Matlab, Python); Proficient communication skills in spoken and written English. Writing experience and experience with bifurcation analysis is considered a plus. Our offer A PhD position
-
to announce a joint open PhD position in Improving Machine Learning Methods for Contingent Claim Pricing and Hedging. The project will focus on, but will not necessarily be limited to, a promising relatively
-
systems with a specific focus on AI and machine learning-based approaches, research, develop, and validate scheduling, optimization, and adaptation algorithms for distributed data-centric computing systems
-
Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as leadership for academic staff
-
learning and mechanistic modelling? We invite enthusiastic and dedicated candidates to join our cutting-edge research team as a PhD student to work on modelling plant life-history traits such as flowering
-
towards improving plant yield under suboptimal conditions. As part of the larger CropXR consortium, you will also collaborate with additional PhD students working on machine learning and mechanistic
-
PhD Cognitive Neuroscience: "The Influence of Predictions on the Mechanisms of Conscious Perception"
Stein, and colleagues. The conscious brain lab consists of several PhD students, postdoctoral researchers and staff members of departments of Psychology of the UvA and VU university, who all study the
-
, accurate response prediction models need to be developed. We are building a dynamic model based on data from serial liquid biopsies, tissue and imaging. Preliminary evidence suggest that machine learning