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or PhD in Computer Science, Data Science, Artificial Intelligence, or a related field. Proven experience in large/small language model development or AI-enabled software development Strong programming
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Responsibilities: Design and develop statistical methods for high-dimensional omics data, including multi-level data (subject, tissue, single-cell) with or without spatial features. Analyse large-scale omics
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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systems Experience in large-scale data processing, signal analysis or real-world system deployment Proficiency in programming (e.g., Python) and ML frameworks (e.g., PyTorch, TensorFlow) Experience with
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management. This is a full-time on-site position located in Singapore. The successful candidate will be responsible for conducting research, performing data collection analysis, and contributing to academic
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. Key Responsibilities: Design, adapt, and apply statistical, computational, or AI-based methods for metabolomics and multi-omics data analysis. Analyse large-scale metabolomics, proteomics
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analysis tools for the large data stream of HTP phenotyping for assessment of abiotic and biotic stress tolerance (e.g. determine extent of damage to a disease or functional response to humidity); also
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-grade codebases, including data pipelines and analysis workflows. Developing and deploying AI agents and large language model–based tools for tasks such as document processing, information extraction
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, large language models, prompt design, adaptive systems, data analysis, experimentation, and research software prototyping. Ability to translate research concepts into practical technical designs
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reviews Lead the analysis of large-scale population level data sets using statistical and data science techniques Provide statistical and mathematical modelling advice to junior researchers Lead the writing