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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data
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hundreds of samples from multiple independent marine transmissible cancer clones. The role provides an exciting opportunity to combine single-cell cancer genomics with molecular cytogenetics and statistical
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work
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responsibilities of the successful candidate will include: Corpus transcription, annotation and analysis of audio recordings from teacher talk in primary school classrooms from different sites in India. Statistical
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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reporting statistical analyses including model development and sharing of open code. - Lead on research publications and outputs, writing first drafts, as well as collaborating with colleagues to support
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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lab investigates systems neuroscience questions, specifically the role of cortico-subcortical loops in statistical learning. We focus on the auditory system and perform awake/asleep electrophysiology
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good understanding of biomedical signal processing Proficiency in Python coding Knowledge of statistics and physiological signal analysis Good understanding of photoplethysmography and Near-infrared