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Field
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Analysi s Experience analysing high-dimensional biological datasets. Proficiency in R for statistical analysis, visualization, and reproducible data analysis. Experience with packages such as Seurat
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(especially: optics, opto‐mechanics, opto‐electronics, RF‐electronics) - good knowledge of analog and digital electronics - programming skills (preferably Python), databases, data visualization, and
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, Gensim, BERTopic, TensorFlow, PyTorch, and LLMs; Advanced in data visualization using Matplotlib, Seaborn, and ggplot2, and experienced in managing research projects with tools like Git/GitHub, ClickUp
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Framework for Medical Device Surveillance https://reporter.nih.gov/project-details/11091149 · CardioOnco-AI: AI-Empowered Cardiotoxicity Risk Prediction Among Breast Cancer Survivors Using Multi-Site
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. * Analyzing brain neural circuits and cellular functions (including nsRNA-seq) in brain regulation from the retina via the non-visual receptor OPN5, which can be applied to conditions such as depression
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explains the underlying concept). 2. Dynamic Narrative Generation and Content ‘Skinning’ a. Investigate the use of Generative AI to alter not only the text but also the visual aesthetics of the materials
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material flow analysis, life-cycle assessment, and techno-economic screening to evaluate selected symbiosis pathways. Preparing technical briefs, maps, diagrams, scenario portfolios, and visualizations
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(longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses, time series
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RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate. 2.) Apply
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; lip-sync and audio-visual synchronization; evaluation of factuality, citability, WER, MOS and latency; software engineering, version control, containerisation or development pipelines; technical