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. Strong programming skills with proficiency in Python and/or C++, and practical experience with deep learning frameworks such as PyTorch or TensorFlow. A track record of high-quality research outputs
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, Python (Programming Language), Researching, Results Reporting, Scientific Writing, Work Collaboratively, Working Independently Questions For frequently asked questions about the application process, please
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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and programming experience (e.g. R, Python) are required. Experience with psychophysiological methods, such as eye tracking and skin conductance, is advantageous. Excellent academic merits, including
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python
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, such as R, Python, or Machine Learning, to identify patterns in biological factors, disease and mortality; co-supervising and mentoring PhD candidates, MSc and BSc students; collaborating with national and
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with mouse genetics, molecular biology (including functional genomics) and bioinformatics (including UNIX, R and Python for single cell analysis). You will be highly motivated, current with
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transcriptomics. You possess strong programming skills in Python, R, or another relevant language. Your experience includes working with bioinformatics tools and databases, as well as multi-omics data integration
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judged from published papers or publicly available (e.g., arXived) preprints, will be given priority. Strong programming skills in R/Python/MATLAB with some knowledge of C/C++ will be preferred. Prior
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confidence and a proven track record using common coding languages (e.g., Python, Matlab, Fortran) expertise and a publication track record in numerical geoscience modelling, such as, but not limited to plate