PhD Position in Geometric Deep Learning: Exploring Symmetries in Neural Networks

Project OverviewThe project aims to deepen the mathematical theory of geometric deep learning. This involves developing new ways of constructing equivariant networks, describing the resulting models mathematically, and analyzing how symmetries affect the training of neural networks.Key ResponsibilitiesConduct research in geometric deep learning and its...

Project OverviewThe project aims to deepen the mathematical theory of geometric deep learning, a subfield of neural network theory that concerns symmetries in data or learning tasks and constructing neural networks that react properly to them.Key Research QuestionsDevelopment of new ways of constructing equivariant networksDescription of the resulting models...

Project OverviewThe project aims to deepen the mathematical theory of geometric deep learning, a subfield within neural network theory that concerns symmetries in data or learning tasks and constructing neural networks that react properly to them.Research QuestionsDevelop new ways of constructing equivariant networksDescribe the resulting models...

Project OverviewThe project aims to deepen the mathematical theory of geometric deep learning, a subfield of neural network theory that concerns symmetries in data or learning tasks and constructing neural networks that react properly to them.Research QuestionsDevelop new ways of constructing equivariant networksDescribe the resulting models...

Project OverviewWe are seeking a highly motivated and skilled PhD student to join our team at Umeå University in the field of deep-learning conifer genomics. The successful candidate will be involved in the development of novel deep-learning driven computational tools for efficient identification of transposable elements in large plant genomes.Research...

Project OverviewAs part of our ongoing research in plant genomics, we are seeking a highly motivated PhD student to join our team at Umeå University. The successful candidate will work on developing deep-learning driven computational tools for efficient identification of transposable elements (TEs) in large plant genomes.Research ObjectivesDevelop new...

Project OverviewAdvances in high-throughput DNA sequencing technologies have led to the production of large genome assemblies, including those of conifers, wheat, axolotl salamanders, and giant lungfish. Genome annotation, particularly the identification of transposable elements (TEs), presents a significant challenge in analyzing these large genomes. Deep...

Project OverviewHigh-throughput DNA sequencing technologies have led to the production of large genome assemblies, including those of conifers, wheat, axolotl salamanders, and giant lungfish. Genome annotation, particularly the identification of transposable elements (TEs), presents a significant challenge in analyzing these large genomes. Deep-learning...

Project OverviewAs a PhD student in plant science, you will contribute to the development of deep-learning driven computational tools for efficient identification of transposable elements in large plant genomes. This project aims to advance our understanding of the complexities of transposable elements in plant genomes and their impact on genome...

PhD Research Position in NeurophysiologyWe are seeking a highly motivated PhD researcher to join our team at the Department of Medical and Translational Biology at Umeå University. The successful candidate will have the opportunity to work on a PhD project in neurophysiology, focusing on sensorimotor control and proprioception.Description of the PhD...

Project OverviewThe project focuses on plant genomics and the development of deep-learning driven computational tools. The goal is to develop new deep-learning driven transposable elements (TEs) identification tools to further decrease the computational demand for large genome analysis.Key ObjectivesDevelop a comprehensive TE dataset to capture the sequence...

Project OverviewThe project aims to develop privacy-aware machine learning models that are explainable and extracted from complex and heterogeneous data. We are interested in building models that provide provenance, interpretable, and transparent results. Within explainable machine learning, we focus on topics such as provenance, interpretable, and...

PhD Position in Medical ScienceWe are seeking a highly motivated and qualified candidate to join our research team as a PhD student in Medical Science with a focus on Neurophysiology. The successful candidate will have the opportunity to work on a cutting-edge project investigating the role of muscle spindles in sensorimotor control.About the ProjectThe PhD...

PhD Position in Medical ScienceWe are seeking a highly motivated and qualified candidate to join our research team as a PhD student in Medical Science with a focus on Neurophysiology. The successful candidate will have the opportunity to contribute to cutting-edge research in the field of sensorimotor neurophysiology and work closely with our team of...

About the ProjectThe project aims to develop privacy-aware machine learning models that are explainable and extracted from complex and heterogeneous data. We are interested in building models that provide provenance, interpretability, and transparency. Within explainable machine learning, we focus on topics such as:Provenance: understanding the origin and...

Research OpportunityThe 'Ultrafast Nanoscience' group at Umeå University invites applications for a PhD position in experimental physics. The successful candidate will contribute to research on ultrafast spectroscopy in condensed matter nanosystems, exploring the dynamics of electronic degrees of freedom in nanostructured materials.Key...

Research Project: Ultrafast NanoscienceThe Ultrafast Nanoscience group at Umeå University invites applications for a PhD position in experimental physics. The project focuses on understanding the dynamics of electronic degrees of freedom in nanostructured materials using ultrafast spectroscopy and plasmonic excitations.Key Responsibilities:Design and...

{"title": "Research Opportunity in Ultrafast Nanoscience", "subtitle": "PhD Position in Experimental Physics", "text": "We are seeking a highly motivated PhD candidate to join our research group in ultrafast nanoscience at Ume\u00e5 University. The successful candidate will have the opportunity to work on a cutting-edge project that interfaces exciting...

Project OverviewThe project aims to develop privacy-aware machine learning models that are explainable and extracted from complex and heterogeneous data. We are interested in building models that provide transparency and interpretability, as well as different types of privacy measures and models.Research GroupThe research group is part of the Computing...

Project OverviewThe project aims to develop privacy-aware machine learning models that are explainable and extracted from complex and heterogeneous data. We are interested in building models that provide transparency and interpretability, while ensuring the privacy of sensitive information.Research GroupThe research group is focused on developing innovative...