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devices; evaluate and integrate new analytical instrumentation. Testing & Characterization: Design and execute experiments to evaluate mechanical, thermal, and chemical properties; analyze data to inform
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of electro- and photochemical modalities into digital chemistry frameworks employing analytical feedback for the acceleration of chemical discovery. The successful candidate will be required to make a leading
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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-oriented researcher who is committed to producing careful, high-quality technical work. The primary responsibility of this role is to plan and execute field measurements and analytical investigations of lift
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem
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, Statistics, Image analysis Basic understanding of plant phenotyping and analysis of large data sets, preferably also using AI tools for image analysis Strong analytical skills and ability to work independently
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systems or autonomous AI frameworks · Solid foundation in computational biology · Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX) · Strong analytical, problem solving, and communication
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Requirements: PhD in Data Science, Computer Science, Biomedical Informatics or related field At least 3 years of relevant experience in data science or analytics role Strong analytical and problem-solving skills
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14 Mar 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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(SingFarm)—a CREATE-NRF programme focused on building a sustainable, data-driven food production model with strong industry relevance to contribute Singapore’s ambition in achieving 20 per cent local