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language processing), machine learning, or data science. Preferred Qualifications Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3
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of the field through the development and use of machine learning, deep learning, and high-performance computing (HPC). This position resides in the Chemical Separations Group in the Separations and Polymer
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calculations, reactive empirical force fields, chemical dynamics, deep learning and numerical algorithms, data analysis, experimental characterization and imaging. Our research has involved methodology and
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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methylation sequencing, single cell DNA methylation, and single cell transcriptome • Perform machine learning/deep learning analyses; and delivering analytical results. • Develop workflows for multiple
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university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity
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The position's field of research focuses on developing and implementing safe, transparent, and explainable AI systems using multimodal deep learning and Large Language Models (LLMs) for healthcare
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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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and analysis, human-machine interaction, productivity monitoring, and proactive personalized feedback and learning methods (using augmented and/or virtual realities). We seek excellent candidates with
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
Experience in Deep Learning and Foundation Models Prior experience with interferometric SAR data sets in forest regions German language knowledge Further Information The AWI is characterized by The AWI is