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. Proficiency in R and Python; comfortable on Linux clusters. Bonus points for Julia or cloud‑native workflows. Proven analytical reasoning—able to translate numbers into biological insight. Desire to innovate
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cancer genomics and functional interpretation of genetic variants Proficiency in Python, R, or other bioinformatics languages Knowledge of cloud computing, and high-performance computing (HPC) environments
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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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computing with Python and R; (d) experience in high-performance and cloud computing for data processing; (e) the ability to work independently and collaboratively with an interdisciplinary research team
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scripting and cloud computing Willingness to learn new languages and tools as the field grows SUPERVISORY RESPONSIBILITIES: This position will involve co-mentoring of students and other researchers joining
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Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing Knowledge of synthetic biology or regulatory sequence design Previous
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attacks, SQL injection, and cheating. Experience in multiplayer game services such as Azure PlayFab, AWS GameLift, Google Cloud Servers, and other similar services. Strong knowledge in C++ will be
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§ Clinical metadata harmonization across cohorts § Integration of clinical and multi-omic microbiome data. § Experience with Python/R and cloud computing preferred Ideal candidate: A computational
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: Experience with generative AI deep learning and active involvement in data science and machine learning projects. Experience in neural network architecture, cloud computing, and database development and
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Responsibilities: Develop and maintain codebases Do experiments to measure and evaluate performance of cloud systems Read and write related academic papers Engage in and facilitate teamwork Co-supervise UG students