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Field
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. Knowledge of Python, C++, Matlab or ROS would be of benefit. The project involves extensive fieldwork, and candidates should enjoy working outdoors. How to apply Please submit a CV and cover letter with your
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or Python are highly desired. Personal qualities: We seek a candidate who is intellectually curious, creative, resilient, meticulous in their research, and has a collaborative spirit. Employment in
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. Experience in statistical packages (SAS), R, Python, or similar programming skills. Point of Contact Janeen Eligibility Requirements Citizenship: LPR or U.S. Citizen Degree: Doctoral Degree. Discipline(s
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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include strong skills in GIS, large dataset handling, Python programming, and a record of scientific publications in the field. Excellent command of English, both spoken and written, is expected. Merits
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author publication(s) in journals relevant in your field and/or shared as preprints Strong statistical foundation and expertise in R or python for data analysis Fluent in written and spoken English and
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blow moulding. You will also have: Experience applying AI or coding tools (e.g. Python or MATLAB) to analyse scientific data A track record of conducting and interpreting experimental work The ability
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machine learning and/or image analysis/computer vision A solid and documented background in machine learning, mathematics, linear algebra, and/or statistics Documented knowledge and experience in Python
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of recurrent neural networks would be a plus; Strong programming skills (e.g., Python, MATLAB or C/C++) are required. Experience with scientific libraries would be a plus. The position is for an initial
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studies, QTL studies, colocalization, Mendelian Randomization) Proficient in R, Python, Linux/Unix Command over commonly used genetics (e.g., PLINK, GCTA, FUMA, variant predictor tools) and metagenomics