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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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data from major facilities, including NASA’s Kepler, TESS, and JWST missions; ESA’s Gaia mission; and large-scale spectroscopic surveys such as LAMOST. Experience working with large, complex datasets is
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, MATLAB and R • Experience in spatial analysis • Experience in using large-scale data sets • Have strong publication records • Excellent scientific writing and communication skills More
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to critic, test-bed and facilitate large-scale, community-based service innovations through a variety of methods including programme evaluation and social analytics The Research Fellow will join a dynamic
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studies. • Plan and execute experiments; analyse and interpret research findings and large-scale biological data (e.g., genomic, transcriptomic, microbiome) and familiarity with following analyses – sc
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studies. • Plan and execute experiments; analyse and interpret research findings and large-scale biological data (e.g., genomic, transcriptomic, microbiome) and familiarity with following analyses – sc
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data collection and research plans Establishing and the management of large databases Interpretating and analysis of data, utilising an array of methods and modelling techniques Generating reports and
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, Public Health, Climate Science, Data Science, or related disciplines. Demonstrated experience in managing large-scale data sets and conducting health-related research studies. Strong analytical skills with
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. Technical Skills: Proficiency in medical statistics, data science, and applications across various domains. Skills in processing and analyzing large datasets, data wrangling, visualization, big data analysis
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with time-series data. The role involves conducting research on multimodal learning and leading technical development efforts within the project. Qualifications Applicants should meet the following