96 programming-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions at National University of Singapore
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datasets; ability to integrate multi-source observational data. • Strong programming skills • Good publication record in relevant journals. • Strong written and oral communication skills
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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disorders, and the role of the gut microbiome in these conditions. Independently design, plan, and execute experimental research aligned with project objectives. Write and review research papers, present
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the genetic and molecular underpinnings of motor neuron degeneration. The successful candidate will be tasked with designing and managing a comprehensive research programme aimed at elucidating the mechanisms
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. The Research Fellow Programme at CIL offers a valuable opportunity to collaborate with and learn from other scholars and experts within the CIL Oceans Law and Policy Team, in a dynamic and supportive research
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is required Proven proficiency in statistical or programming software (e.g., SPSS, R, STATA, Qualtrics), with evidence of applied research outputs Additionally, you will be favourably considered if you
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both infectious and chronic disease, measuring the impact of interventions. Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming
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: • Statistical programming and data analysis using R, Python, Stata, or similar tools • Experience with machine learning or AI methods for health data analysis • Experience working with large health datasets
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electronics/electrical engineers, you will be part of an exciting research program to develop next-generation sensor devices and systems for human-machine interactions. Qualifications PhD in Materials Sciences
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generation sequencing studies. Assist researchers in programming and data analysis. Perform analysis of complex and large-scale genomics data, including (but not limited to) WGS and transcriptomic data