187 electric-machine-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions
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Field
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. Apply advanced statistical, econometric, and/or machine learning methods to analyze complex health datasets (e.g., claims, EHR, hospital discharge, survey data). Prepare manuscripts for peer-reviewed
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: 35* Days Annual Leave (pro rata if part-time) plus Bank Holidays* & Closure Days* Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance Programme Development opportunities
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solutions that improve access, experience, outcomes and equity for patients and families. For more details, please view ntu.edu.sg/pcfm and https://www.ntu.edu.sg/medicine/research/office-of-patient
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systems). Current activities and themes include the following: (1) Mapping homologies in the gastrulation system across gnathostomes and understanding how different gastrulation modes evolved; (2) tracing
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annual leave: 35 Days Annual Leave plus Bank Holidays & Closure Days Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance Programme Development opportunities Enhanced family
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repair on RNA-DNA hybrids of R-loops using computational modeling and molecular dynamics simulation along with various types of AI tools and machine learning approaches. Temporary Expertise in
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, morphodynamic, and landscape evolution models. Field experience in geomorphological and hydrological surveys, including the use echosounders and Acoustic Equipment Use of personal computer and proficiency in
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page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https
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) plus Bank Holidays* & Closure Days* Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance Programme Development opportunities Enhanced family leave Flexible working Retailer
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, quantitative characterization, and machine learning-enabled decision-making. The position is associated with the recently awarded ERC Consolidator Grant project “Engineering Multivalency for Superselective