candidates to pursue a PhD degree in machine learning. The successful candidate will be supervised by professor Aristides Gionis... for machine learning, analysis of information and social networks, fairness, accountability, and transparency in learning systems...
candidates to pursue a PhD in machine learning at KTH, Sweden, and NTU, Singapore. This is a fully funded, joint doctoral... in Singapore as part of the joint program. The research project is broadly situated in the field of machine learning. Potential...
of these. We seek a candidate who have experience working with time series data (EEG), signal processing and machine learning... with computer vision, machine learning and video processing. Supervision: Professor Danica Kragic is proposed to supervise the...
optimal transport and gradient flows to machine learning and optimization applications, such as deep generative models... machine learning. The goal is to build a theoretical and computational foundation for new methods in statistical inference...
Project description Third-cycle subject: Computer Science PhD students will work on robot learning for manipulation... with a strong background in robotics and machine learning, and demonstrated experience in two or more of the following areas: deep learning...
to construct more reliable 3D structures. The results are expected to be published at top machine learning venues such as NeurIPS... knowledge, strong programming skills, esp. deep learning, prior education and research experience in machine learning...
Anemometry or Particle Image Velocimetry is a merit. Experience with Machine Learning is a merit. After the qualification... challenges in sustainable city design. Supervision: is proposed to supervise the doctoral student. Decisions are made...
, combining statistical, machine-learning-based, and data-intensive approaches with qualitative and participatory foresight... must have documented knowledge of quantitative methods, such as statistics, econometrics, data analysis, machine learning, and forecasting...
. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection... and developing new machine learning models, specifically generative ones, and publishing the results at top machine learning venues...
with stakeholders beyond project partners and academia. The candidate will collaborate with other doctoral students in the research..., for instance in applied math, transport science, computer science, machine learning, AI documented programming skills, for example...
representatives Contact information for Doctoral Students`network (Students’ union on KTH Royal Institute of Technology) Contact... multiplexing, and integrated communication and sensing (ISAC). In this doctoral project, you will contribute to cutting-edge 6G...
criteria for third-cycle (doctoral) studies. Interest or experience in areas such as machine learning, data analysis, battery..., and operational data. The doctoral student will develop battery aging models tailored to the project’s case studies using transfer...
(e.g., Python, MATLAB) and experience with machine learning/deep learning. Background knowledge in kidney biology, cell...Do you want to contribute to top quality medical research? To be a doctoral student means to devote oneself...
and Control Systems at KTH. Our group conducts fundamental research at the intersection of machine learning, optimization... expertise in machine learning, control theory, or applied mathematics, demonstrated by publications in high-quality...
-based eco-evolutionary theory, high-frequency in situ monitoring data, and machine learning methods. Using a unique multi... of phytoplankton communities Applying machine learning and scientific machine learning (SciML) approaches to infer fitness and growth...
environment. As a doctoral student at DSV, you study together with many other doctoral students, collaborate with senior research... in critical domains such as healthcare. The project will build on ongoing research in machine learning for structured, semi...
-analysis, satellite data, and analyse those in relation to survey data. This involves methods such as machine learning... and instrumental variables estimation, as well as an application of a machine learning–based extension of the standard difference...
recordings using silicon probes, miniscope, or 2P imaging. Ability to explore and analyze large datasets using modern machine... learning methods and a data-centered approach. Previous participation in collaborative projects with computational...