28 programming-languages-"the"-"CNRS"-"U"-"UCL"-"O.P" Fellowship positions at National University of Singapore
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with the CHILD management and cross-disciplinary research teams and collaborators. Design, plan, undertake and deliver evidence synthesis projects and publications. Lead planning, coordination and
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experience in programming languages such as R, Python, and familiarity with NLP tools and techniques (essential) Proven track record in handling and analyzing large healthcare dataset (essential) Track record
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are seeking for a full-time Postdoctoral Fellow to work on projects in the area of household finance, investment, and financial literacy. The project is part of a large 5-year research program (2024-2028) which
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statistics, statistics programming languages like R, and applied data analysis for social science. Additionally, the RA will also help the Principal Investigator with general administrative assistant work
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program aimed at developing a better understanding of how aging beliefs and mortality expectations may influence economic decision-making among individuals and households. The Principal Investigator
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science, computational biology, engineering, statistics, mathematics.). Experience and interest in prediction modelling Proficient in statistical software and programming languages and familiarity with relevant libraries
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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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-language-action learning, enabling seamless integration from human instructions to robotic actions in complex mobile manipulation scenarios. Qualifications • Ph.D. Degree in a relevant discipline, e.g
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approach to achieve a goal, once a problem statement and/or a research scope is defined by the PI and the staff. The staff will need to execute the plan experimentally and interpret the data critically
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approach to achieve a goal, once a problem statement and/or a research scope is defined by the PI and the staff. The staff will need to execute the plan experimentally and interpret the data critically