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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 14 days ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
Area of research: Laborkräfte Job description: Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic nodule fields (m/f/d) Background While some companies
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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supported by an external team of deep-learning experts. You will also become an integral part of the Multiscale Cloud Physics Group currently being established by Dr Franziska Glassmeier at the Max Planck
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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific