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Field
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prompts Develop predictive models for sepsis, deterioration and ICU outcomes Create reproducible analysis frameworks using R/Python, GitHub, Quarto or R Markdown Produce real-time dashboards for ICU
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scenario analyses to examine how noise might evolve across different technological and operational futures and how it interacts with emissions, policy options and airport‑level constraints. This is a key
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scenario analyses to examine how noise might evolve across different technological and operational futures and how it interacts with emissions, policy options and airport‑level constraints. This is a key
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Join the forefront of groundbreaking research at City of Hope where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses
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motivated Postdoctoral Fellow with strong expertise in RNA-seq and multi-omics data analysis. Candidates should be proficient in Python and/or R and have a solid background in Biology, Computational Biology
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datasets using Python or R. Ability to work both independently and collaboratively, with strong organisation, attention to detail and communication skills. Clear motivation to apply interdisciplinary and
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in high-quality journals. • Proficiency in programming and modelling tools (e.g., R, Python, C/C++, Julia). • Excellent quantitative and analytical skills, with experience handling complex datasets and
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of a team. Ability to meet deadlines and efficiently multitask. Ability to effectively collaborate across a range of individuals with different comfort toward computational biology, including oral and
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microscopy, antibody-based techniques, small molecules/ligand-trap based therapies Preferred qualifications Experience with bioinformatic analysis using R and/or Python. Experience with molecular/cellular
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that significantly reduce computation cost, memory footprint, and power consumption. Design and optimize efficient training and inference pipelines for foundation models (LLM, VLM, VLA) across different model sizes