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position is funded by multiple NIH projects, e.g., https://tinyurl.co m/ysxhmujvThe overall goal is to : (1) develop inference and dynamic prediction models using a wide variety of data, including clinical
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. Applicant must have (or expect to obtain shortly) a Ph.D. in Biological Sciences or related field. Experience with Neuroimmunology and/or Immunology is highly preferred. Proficiency in mouse models of disease
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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the position, the required skillset includes: Strong background in electromagnetic and optical modeling using tools including Ansys, Comsol, Matlab, and other methods. Expertise in wet chemical synthesis
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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of multiple administrative data sets. Conduct data analysis (descriptive, bivariate, predictive, longitudinal, etc.). Write reports for funders and interested parties and prepare manuscripts and presentations
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of multiple administrative data sets. Conduct data analysis (descriptive, bivariate, predictive, longitudinal, etc.). Write reports for funders and interested parties, and prepare manuscripts and presentations
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will develop andapply cutting-edge methods in predictive and causal modeling for age-related maculardegeneration ( AMD ), a primary cause of irreversible vision loss worldwide. This work willinvolve the