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deep learning, optimisation, sampling. Good coding skills for numerical simulation (Pytorch, Python, MATLAB, ...). A general interest in health and biology is welcome. Practical information MORPHEME
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, biomedical engineering, or a related field. • Experience with coding software such as Python, R, or Matlab. • Familiarity with collaborative coding software such as GitHub and database management
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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technologies, is highly desirable. Skills: Strong knowledge of clinical informatics frameworks, standards, and methodologies. Proficiency in data analysis software (e.g., R, Python, SAS, SPSS, SQL) and
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data
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contribute to the development of a proof of concept obtained at University Côte d’Azur for accessing the content of a metabolomics knowledge graph (KG) with a large language model. It is Python prototype of a
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, clustering, classification • deep learning, variational auto-encoding, back-propagation • excellent knowledge of R and Python. The knowledge of C++ would be a plus. Application: Application files should
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skills in at least one relevant language (e.g., Python, R, Rust, JavaScript) Familiarity with smart contract interaction (e.g., web3.py/ethers.js, Solidity/Vyper, sub-graph indexing), and local development
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
to clinical applications. ➢ A good knowledge of Python, TensorFlow, PyTorch environments, and segmentation software such as 3D Slicer is expected. ➢ Skills in knee anatomy, CT imaging, as well as an interest in
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Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) preferred, Knowledge and Skills : Expertise in Python with libraries (e.g., Pandas, NumPy, scikit-learn, TensorFlow, Keras, spaCy