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A two-year postdoc position is available in the research group of Algorithmic Cheminformatics at the University of Southern Denmark (SDU). The position is in an exciting 6-year project supported by
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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
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computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET
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algorithms, NLP models, and LLMs to analyze complex data. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune