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bioinformatics tools for integration of multi-omics and gene regulatory networks. The long-term research goal is to answer the key scientific question “How non-coding genetic variant act through context specific
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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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working experience with healthcare data (e.g., EHR, clinical text, imaging, omics). Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g
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with omics data analysis, biostatistics, and image analysis tools. Strong programming skills (R, Python) and knowledge of relevant databases and pipelines. Candidates with peer-reviewed publications
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or interest in the use of artificial intelligence, machine learning, or computational tools in behavioral and experimental economics is appreciated. Strong emphasis will be placed on demonstrated research
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data collection and integration across multi-institutional collaborators. Work closely with clinical and research teams to ensure high-quality sample tracking, annotation, and compliance with
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. Familiarity with scRNAseq, bioinformatics tools, and the analysis of large datasets is desirable but not required. If you are enthusiastic about pursuing innovative research in pediatric HIV and immunology and
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until position is filled. Contact: Dr. Gunther Jikeli (gjikeli@iu.edu) Note: This position involves research on sensitive topics and may require handling potentially disturbing content. Indiana University
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projects. Current doctoral candidates are welcome to apply but must defend their dissertation prior to the start date. Please note the anticipated or confirmed completion date in the cover letter. Department
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projects. Current doctoral candidates are welcome to apply but must defend their dissertation and confer their degree prior to the start date. Please note the anticipated or confirmed completion date in