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Field
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infrastructure.Undertake fieldwork in tropical North Queensland. Perform and image behavioural presentations. Extract and analyse 3-dimensional object tracking data. Lead the preparation of high impact scientific
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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
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reputed refereed journals and presenting at conferences. Technical expertise in programming (e.g. python) and experience with high-performance computing are highly desirable. Experience in machine learning
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, cell-based assays, animal work, histology, PCR, and possibly Western blotting, and flow cytometry , ensuring high standards of accuracy, reproducibility, and documentation. Troubleshoot, operate, and
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datasets, performing statistical analyses and machine learning approaches to identify biomarkers of treatment responses. The candidate will also develop and implement bioinformatics pipelines in a high
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seals. Seals are among the most elite diving mammals with remarkable adaptations to low oxygen and high carbon dioxide exposure at levels that would cause serious harm to people. This work, at the cutting
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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, Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and Information , Data Visualization , Deep Learning , High dimensional Data , Large Language
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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skills. Demonstrated ability to work independently and as part of a team with minimal supervision. Demonstrated capacity to deliver high-quality project outcomes in a timely manner. Computer programming