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working with genomics data sets. Prior experience working on high performance computing clusters. Prior experience with statistical and mathematical modeling and/or AI. Type Benefited Staff Special
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universities. analyse various vehicle architectures and configurations with special emphasis on the two-stage-to-orbit (TSTO) vehicle based on LOx-methane cryogenic liquid propulsion, engine clustering, low
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students, and senior scientists, all working together in a collaborative environment. Qualifications Ideal candidates will have: A PhD in Genetics Bioinformatics, Computer Science, Data Science, Statistical
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developing and implementing very large deep learning models. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems
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with observations from large surveys and optical/near-IR telescopes including SDSS-APOGEE, GALAH, GECKOS, and the upcoming 4MOST project. We encourage applications from all who have interests, skills
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computing clusters and analysis of transcriptomics and genomics datasets. Desirable Requirements Experience in single-cell and spatial OMICS data analysis. Development of ShinyApps and
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of existing ones for scientific applications; (ii) Large Language Models (LLMs) and multi-modal Foundation Models (iii) Large vision-language models (VLM) and computer vision techniques; and (iv) techniques
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life – including the explosion of large language model (LLM) releases. BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications and uses
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industry, education, and public life – including the explosion of large language models (LLMs). BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications
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(e.g. Python, R, …). Familiarity to work on a Linux computing cluster (HPC). Preferably experience in working with large medical image data. Vivid interest in the analysis of microscopy images or similar