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function and promote healthy aging. Our laboratory combines mouse genetics, genome engineering, advanced microscopy, quantitative image analysis, single-cell and spatial multi-omics, biomaterials, and
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, biostatistician, clinic staff, and principal investigator in their research efforts; attends research team meetings; assists with analysis of research results; participates in planning, designing, and execution
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certain type of treatment, with potential impact in clinical practice and cancer research. This position is linked to the project BIOEURECA:Next-gen biomarker discovery: foundation models for tissue spatial
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-seq, and spatial transcriptomics, to investigate gene expression and cellular dynamics in lung development and disease. This role involves close collaboration with bench scientists to design experiments
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
spatial multi-omics data; AI-based modeling of protein structure and protein interaction networks; AI-based modeling of cell morphology and tissue function using imaging and computer vision; AI models
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, or equivalent) conferred by the start date. 2. Proficiency in R/Python. 3. Experience with spatial proteomic/transcriptomic data analysis. 4. Growth mindset and motivation to advance our understanding of breast
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Particular focus will be placed on deriving velocity and flow depth estimates at unprecedented spatial and temporal resolutions by analyzing point cloud and camera data You will develop a deep understanding of
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on understanding the earliest stages of high-grade serous ovarian cancer (HGSOC) by integrating spatial multi-omic profiling with computational analysis to define how precancerous lesions evolve into invasive
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in computational methods and/or quantitative methods, primarily spatial analysis. Experience in supervising and managing research groups. Experience in conducting academic research related to analyzing
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The Ho Lab at Yale University School of Medicine (https://medicine.yale.edu/lab/yachiho/ ) is recruiting motivated, productive, independent, and collegial postdocs interested in viral infection, T