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Field
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our industrial partners. You will work in the cyber analytics and CISE labs in the Algorithmics and Software Engineering Research groups at the Software Technology department under supervision of dr
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with the rest of the team, you will build demonstators for the Find2Fix technology at our industrial partners. You will work in the cyber analytics and CISE labs in the Algorithmics and Software Engineering
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for Biomarker Discovery: Develop and fine-tune machine learning algorithms for biomarker discovery, cancer classification, and exploring omics features. Collaborative Research: Work in a multidisciplinary setting
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Requirements Collaboration with the project team to carry out research activities, including reports, studies and scientific articles; Creation of algorithms, code snippets and development of statistical methods
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key
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team. Significant software development experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication
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of Norway (RCN) and are supported by the Centre of Excellence funding Scheme by the RCN (the Centre for Algorithms in the Cortex), as well as the Kavli Foundation. The Zong group is further supported through
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon