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Field
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that includes medical image processing, Artificial Intelligence (AI) algorithm development, and scientific writing. Gain clinical experience including training in radiation oncology software, imaging including
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. The successful candidate will pioneer new algorithms for graph-structured data, revisit classical graph problems through the lens of modern machine learning, and help define the next generation of generative
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differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic Qualifications Candidates are required to have a doctorate or terminal degree in Computer Science
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RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate. 2.) Apply
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point cloud techniques for geometric analysis; (b) develop and implement algorithms for 3D perception; (c) design and execute experiments to evaluate validate and refine algorithms and systems; (d
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. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic modeling
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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of detailed protocols including operational definitions, data dictionaries and ICD/CPT codes used for algorithms; will be responsible for making statistical analyses code publicly available on GitHub ensuring
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain
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environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software