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-reviewed journals Experience with one or more scripting language (e.g., R, Python, SAS) and/or genetic software (e.g., DMU, ASReml) Can biologically interpret results and relate to breeding decision making
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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. The ideal candidate will also be expected to have quantifiable experience with: A variety of different neuroimaging methodologies. Using multiple programming languages, including R, Python, MATLAB and
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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-on experience in training large neural networks (generative models). Hands-on experience in medical image reconstruction. Preferred Qualifications: Proficiency in Python, C/C++, and Unix-like operating systems
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publication record in top-tier venues: ICRA, IROS, RA-L, T-RO, IJRR, CoRL, NeurIPS, RSS, CDC, TAC. Proficiency in Python, C++, ROS, and machine learning frameworks such as PyTorch or TensorFlow. Excellent
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scientific communication proficiency in one or more coding languages (e.g., Python, R, Matlab, or equivalent) strong interpersonal skills and the ability to work collaboratively within a diverse research team
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record of publications in leading international scientific journals (Q1) and effective scientific communication proficiency in one or more coding languages (e.g., Python, R, Matlab, or equivalent) strong
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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plus Expertise in programming (C++ and Python) Special Instructions to Applicants: For full consideration, applications must be submitted online. Click on Apply Now at the top of this posting. A complete