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of large and complex data sets, spanning brain imaging, genetics and clinical data. The goal is to reveal more of the genetic architecture underlying brain structure and function and to improve our
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dual focus on method development and application on large-scale data sets, with the balance dependent on the candidates’ skills and interests. We have access to thousands of whole-genome-sequenced cell
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learning paradigms as well as interactive data- and model exploration with domain knowledge towards optimal performance in real-world generalization scenarios. AqQua is a large-scale collaborative research
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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cohorts. Duties The project combines single-cell, multi-omics data with large scale human genetics to investigate the cellular origin of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD
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associate. We are conducting several large randomized clinical trials, cohort studies, and surveillance programs, in India, Latin America, and the United States related to nutrition, infectious diseases, and
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grants, as well as the management of large clinical datasets. Job Description: Job Duties Outlined Research Overview: Design and conduct experiments and interpret data under the mentorship of the Principal
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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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selection models that will be applied in ongoing domestication and plant breeding efforts. You will work with large genotypic and phenotypic datasets and apply biometric approaches on different selection
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team and for independent funding. Thus, we welcome applicants with experience in large volume serial electron microscopy (connectomics), synchrotron source X-ray imaging of brains in health and disease