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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
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the molecular level. While structural predictions using deep learning methods like AlphaFold have revolutionized our understanding of sequence dependent molecular structure, we currently have much more limited
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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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/ Ecology Appl Deadline: 2025/07/31 11:59PM (posted 2025/05/21, listed until 2025/07/31) Position Description: Apply Position Description The Cordes Lab in the Department of Biology at Temple University is
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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deep learning methods to enhance the predictions beyond existing data. By incorporating microstructural features into predictive models, the aim is to create a reliable data-driven modelling framework
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre