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Essential Requirements: - PhD Degree in a relevant scientific field (e.g. computer science, data science, mathematics, engineering, or related); - Strong understanding of generative models (e.g., VAEs, GANs
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, communication algorithms) Parallel programming models and runtimes for emerging architectures (e.g., processing-in-memory, SRAM-centric) Performance modelling & optimisation of ML algorithms on unconventional
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, spectral matching against databases (e.g., Metlin, KNAPSAcK), and statistical modeling for biomarker discovery. Integration and Interpretation: Correlate metabolomics data with biological and geographical
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