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optimization techniques. You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming. Knowledge of, or prior experience with, optimizing
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interdisciplinary team. Tasks: Assembly and annotation of phytoplankton genomes and metagenomes Further development of bioinformatic data analysis pipelines Use and further development of deep learning tools
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model we deploy and support the ecosystem with training, advisory, and AI infrastructure. CeADAR is seeking a data scientist with solid experience in machine and deep learning research and development
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning
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[map ] Subject Areas: Mathematics, AI-based drug design and discovery, Bioinformatics/Protein Engineering/Single-cell Omics Data, Mathematical AI/Machine Learning/Deep Learning, and Computational
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needs. Project background We are excited to announce an interdisciplinary PhD opportunity focused on mechanochemical processes driving radical formation and redox cycling in the deep subsurface, with
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quantitative field. Strong background and expertise in data science, bioinformatics, network science, artificial intelligence, machine learning, deep learning, or related areas. Solid understanding of AI
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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of machine learning and deep learning methods and classification of health and wellness parameters. Data acquisition, as well as the preparation of presentations, scientific publications, and technical reports