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for scalable qubit architectures. Qualifications · For Theorists: o PhD in quantum information, theoretical physics, computer science, or related fields. o Strong background in quantum algorithms, error
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Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc trainees in
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. The PhD candidate will join the team Methods and Algorithms for Bioinformatics (MAB). - Supervision: - Dr Eric Rivals, HdR, (LIRMM), CNRS Research Director in computer science and bioinformatics (web https
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, enabling algorithm–circuit co-optimization across the computing pipeline with respect to key metrics such as power consumption, computational delay, and area efficiency. Beyond circuit prototyping
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about the lab at: https://mbzuai.ac.ae/study/faculty/natasa-przulj/ and https://przulj-lab.github.io/ Qualifications PhD in Computer Science, Mathematics, Physics, Bioinformatics, or a related
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algorithms that significantly reduce computation cost, memory footprint, and power consumption. Design and optimize efficient training and inference pipelines for foundation models (LLM, VLM, VLA) across
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 8 hours ago
General Summary of the Position Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865 ). The Zhou Lab at UMass Chan Medical
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and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product. The post-doc project is about extending the biomass algorithm to also include data
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limited to synthetic and chemical biology approaches to cellular computation and biomolecular logic design, the development and implementation of novel algorithms, machine learning for parsing biological