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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and
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reputable journals and conference proceedings in Communication and HCI. Proficiency in quantitative/statistical analysis and computational techniques (e.g., NLP, data mining). Experience conducting mixed
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. Experience in AI system security, adversarial robustness, and resilience of autonomous agents in emerging technologies and computer security (e.g., malware analysis, bug detection, program repair). Excellent
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, plasmonics, or chiral photonics. Experience in biosensor fabrication and testing under biological conditions is highly desirable. Proficiency in experimental design, data analysis, and interpretation
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, FACS analysis, multiplex IHC, spatial transcriptomics (GeoMx DSP), and proteomics Experience with clinical samples and biomarker discovery workflows Excellent communication and lab management skills
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well as developing and implementing novel approaches to answer research questions Scripting and automating robust analysis pipelines Writing of scientific manuscripts Presentation of work-in-progress and results
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handling, storage, and security of genomic and clinical data. Adhere to ethical, regulatory, and institutional guidelines for genetic data analysis Key Competencies and Requirements: PhD degree in
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techniques. Strong background in intermetallic systems, phase diagram analysis, and crystallography. Familiarity with high-throughput or combinatorial synthesis approaches is a strong plus. Experience in
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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and reporting of experimental results and/or research findings. Assist researchers in programming, data analysis and literature review in various research projects. Evaluate and interpret collected data