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Field
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sequencing data analysis, variant interpretation, and bioinformatics workflows used in research and diagnostic settings. Strong programming skills (e.g., R, Python, Perl, C/C++, Bash) and confidence working
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reporting standards * Familiarity with deep learning technologies (e.g., CNNs, transformers) * Experience with Python and ML ecosystem skills (e.g., PyTorch, scikit-learn, etc.). * Skilled in writing and able
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compositionality with large language models. * Strong Python and ML ecosystem skills (e.g., PyTorch, scikit-learn, etc.). * Facility with C/C++/Rust or other systems-level programming languages * Skilled in writing
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also being a mentor to other members of the community. KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED: Background in machine learning Background in cancer biology Experience with R and/or Python Experience
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of algorithm-hardware co-design, especially for robotics or edge AI deployment. Strong programming skills in C, C++, and Python, with experience in deep learning frameworks such as PyTorch or TensorFlow
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computing (e.g. Python, MATLAB, or similar) for data processing and data handling Experience with data processing, analysis and interpretation Excellent interdisciplinary communication – Strong collaborative
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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. Python, MATLAB, or similar) for data processing and data handling Experience with data processing, analysis and interpretation Excellent interdisciplinary communication – Strong collaborative skills
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measurements, awareness of noise, efficiency, and timing trade-offs in low-light imaging. Applicants should have competence in data acquisition/analysis and scripting for instrument control (e.g., Python/Matlab
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datasets. Proficiency in R and/or Python, and familiarity with tools such as Seurat, Scanpy, DESeq2, edgeR, Monocle, or similar frameworks. Experience working with large-scale sequencing datasets and high