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: bioinformatics, breeding, biomaterial synthesis, and cellulose‑processing enzyme design. You will develop hybrid quantum‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods
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to new developments. The candidate will join the System Software Group , and study the performance and scalability characteristics of adapting scientific simulation software to current and future
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of the internship: Machine Learning for recognition of planetary materials from multispectral datasets You are sought to contribute to the ongoing development of Machine Learning algorithms for recognition
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‑processing enzyme design. You will develop hybrid quantum‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods will be designed for near‑term (NISQ‑era) deployment, with
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Engineering Laboratory (HRE Lab), providing the candidate with access to advanced experimental infrastructure and opportunities to contribute to the further development of the laboratory’s research and
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) rigorous evaluation of algorithmic improvements.For some inspiration on this topic, see the CertiFOX project page: https://www.bartbogaerts.eu/projects/CertiFOX/ Another long-standing objective is to
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, quantum science, condensed matter, materials, photonics and interdisciplinary applications of physical science. This role sits within a collaborative quantum science project at King’s on quantum algorithms
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includes the development of a preliminary processing chain featuring phase synchronization, accurate trajectory estimation, time-domain multistatic focusing, and algorithms for the estimation and
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, the Student Assistant develops social media campaigns, captures photo and video content, designs marketing materials, and represents the department at campus outreach and recruitment events. The Student
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, and Rust for speed-optimized algorithm implementations. Projects will entail development of command line tools, APIs, and cloud-based web services (both public and private cloud). Establish and maintain