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Field
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data integration. Knowledge of python and R is essential. This is a full time (35 hours per week), and you will be offered a fixed term contract until 30 June 2027. About You To be successful in
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, or a related field. Expertise in deep learning, multimodal LLMs, and Vision-Language-Action models. Strong programming skills in Python, with significant experience in PyTorch. Hands-on experience with
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development, environmental science fieldwork, electronics design, and data science. Knowledge of Python, C++, Matlab or ROS would be of benefit. The project involves extensive fieldwork, and candidates should
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experience for example with python, fortran, C++ or others. Experience in modeling spectroscopic observables. Experience in quantum and semi-classical dynamics As a founding signatory of the Athena SWAN
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, automatic testing, program synthesis Excellent background and experience in programming language, especially python Good communication and report-writing skills Strong responsibility for research and work We
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of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records. Track
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with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly desirable. Proficient in Python, R, and ML libraries
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bioinformatics tools for microbiome analysis (QIIME2, Kraken2, MetaPhlAn) and AMR gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments
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or Planetary Science, Applied Mathematics, Physics, or a closely related field, completed by the start of the appointment. You should have strong scientific programming skills (Julia, Python, Fortran or C++) and
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++/Python. Excellent communication and collaboration skills. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU