72 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Aalborg University in Denmark
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
have: A relevant PhD degree (e.g., NLP, AI, ML, Security, Cryptography, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence
-
. Mathematical skills: Competence in mathematical modeling of dynamic systems and probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM
-
algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
-
research in Time Series Analysis and Econometrics with focus on one or more of the following key research areas: Nonparametric estimation. Machine learning methods in econometrics and time series analysis
-
modeling, optimization techniques, hybrid testing and digital twins. Furthermore, the position aims at incorporating machine learning to drive innovation in the areas. Possible applications are within
-
obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in
-
obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
-
the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group
-
on the development of AI models for analysis of cardiac CT scans, with the aim to explore how machine learning models can quantify cardiovascular disease and predict future events from CT scans. The project will
-
Biological Learning Machine, which is headed by Professor Jan Østergaard. The goal is to develop novel information-theoretic methods for identifying and analyzing temporal and spatial patterns of synergy and