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and statistical skills, with proficiency in R or Python Experience working with longitudinal data, infectious disease epidemiology, or high-dimensional datasets Demonstrated track record of peer
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project research; - to build or help build scripts (Python or equivalent) to trace the spread of the aforementioned vocabulary in early modern print; - build up a taxonomy of early modern prisca-related
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the following tasks: - to build up a full ‘prisca’ vocabulary in Latin, English, and at least one other language included with the project; - building or help building scripts (Python or equivalent) to trace
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algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models Hold at least a
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analyzing environmental DNA metabarcoding datasets, Use of common bioinformatic pipelines such as QIIME2 and DADA2, Experience in python and R programming languages, Co-authorship of peer-reviewed
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, computational modeling, computer vision, natural language processing, or related AI-based methods. Strong programming skills, preferably in Python. Experience working with complex, multimodal datasets and
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AI and machine learning methods applied to cancer genomics. Proficiency in at least one modern programming language. Experience with a scientific programming environment, such as python or R, is
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. We will also consider candidates who have extensive C++ or Python coding knowledge as these are transferrable to R. The candidate will be working with the Principal Investigator(s) on the analysis
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chemistry preferred) researchers. Track Record: A strong publication record in NLP, ML, Multimodality, Information Retrieval, or Chemistry. Technical Skills: Proficiency in Python and PyTorch/JAX is required
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: Training and hands-on experience in epidemiologic and quantitative data analysis Experience with statistical software such as SAS, R, Stata, or Python Experience analyzing observational, survey, electronic