Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement learning strategies for comb generation
-
focus on the following areas: Subspace tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement
-
and inference with cluster-dependence, high-dimensional parameters, or outliers. Other possibilities could be, for example, theory of bootstrap or nonparametric inference. For more information and
-
work at the intersection of palaeogenomics, bioinformatics, and evolutionary biology to overcome long-standing barriers in analysing degraded or low-quality DNA, enabling reliable genomic inference
-
on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
-
XAI methods, e.g. counterfactuals in reasoning and knowledge graphs (KGs) based on domain expertise, to strengthen inferences drawn from data, and to reduce complexity of learning – by factual reasoning
-
available (>1.1 million people). The goal is to establish how many archaic human groups contributed to our genomes. Your task is to infer key parameters of the archaic human evolutionary history such as
-
observations, have led to an exponential growth in biological data, from genomics to single particle tracking and beyond, enabling scientists to study the intricate workings of living organisms in unprecedented
-
. The PhD project falls under Research Track 1: Informational Modes of Learning. Functional connectivity captures the statistical relationships between distinct brain regions, whereas effective connectivity
-
redundancy in brain signals elicited by acoustic stimuli. The PhD project falls under Research Track 1: Informational Modes of Learning. Functional connectivity captures the statistical relationships between