Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and
-
senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
-
Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
-
the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
-
Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
-
infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
-
. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
-
includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
-
theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
-
/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning