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maintain data for easy retrieval. Uses artificial intelligence and machine learning to develop new methods in computational structural biology Performs structure prediction using AlphaFold 2. Performs in
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learning algorithms. Good computer programming skills in R/Matlab/Perl/Python. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing data and scRNA-seq
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Summary We are seeking a talented individual to work with our team on a project on genetics on lung development in humans and lethal lung developmental disorders in neonates. We invite you to learn
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and apply advanced computational techniques related to statistical genetics, algorithm design, machine learning, artificial intelligence, and knowledge graph construction, data visualization, and/or
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computer skills. Demonstrated willingness to learn new techniques with instruction. Demonstrated strong work ethic, including ability to take initiative, prioritize tasks, use good judgment and complete
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, proactively suggesting and implementing enhancements whenever necessary. Remain at the forefront of data science and machine learning advancements, integrating the latest methodologies and innovations
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aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, a CRISPR/Cas9-based mutagenesis screen will be applied to discover and therapeutically target novel
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. Preferred Qualifications Applicants should have a recent Ph.D. degree in molecular biology, or protein engineering, synthetic biology, electrophysiology, advanced microscopy, optics, and/or machine learning
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resistance and cancer recurrence. Methods range from statistical, computational, to machine-learning based. These new methods are expected to benefit the community at large by being broadly applicable
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experience Strong data analysis skills including exploratory data analysis, statistical testing and machine learning. Experience with bash and scientific programming using Python, R, or Julia. Experience in