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. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in
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, single-unit recordings. 2. Strong background in computation modelling of behavioral or neural data. 3. Proven experience with statistics, machine learning and/or brain stimulation. 4. Proven experience
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for AI and Machine Learning included as well as industrial statistics), which will complement our current research portfolio (see https://stat.kaust.edu.sa) and have a research profile that can potentially
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, test and measurement methodologies for electronic modules, system engineering, data pre-processing and database indexing/analytics for dashboarding/visualisation, embedding machine learning algorithms
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workloads including embedding generation, LLM inference, and cognitive search. Develop Snowpark Python transformations, UDFs, and machine-learning features. Implement vectorized storage, model-serving
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systems in the research project, including testing and troubleshooting. Implement and test machine learning models, which may involve data preprocessing, model training, and evaluation. Create and maintain
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cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and assisting with the communication of scientific
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leverage state of the art machine learning models (AlphaFold2, RFdiffusion) and multi-omics data integration to guide the rational design and optimization of therapeutic antibodies. Overall, you will have
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/10.1016/j.xcrp.2022.101112 and https://doi.org/10.1080/08940886.2022.2114716 key words synchrotron radiation; X-ray Absorption Spectroscopy, machine learning, artificial analysis, autonomous experimentation
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting