Sort by
Refine Your Search
-
. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning
-
generated quickly and regularly. Help develop machine learning techniques for feral swine abundance in data sparse environments. Collaborate with APHIS Wildlife Services (WS) to integrate data and model
-
skills: Experience developing artificial intelligence (AI) or machine learning (ML) models, particularly for time series or spatiotemporal data. Experience with representation learning, anomaly detection
-
to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
-
inference (otherwise known as spectral retrieval), which involves using forward models in conjuction with Bayesian or machine learning-based techniques in order to derive posteriors on parameters of interest
-
. Research Project: A Postdoctoral Fellow will participate in a project focused on analyzing forest change and disturbances on U.S. forests. In this project, we will collaboratively develop one or more models
-
to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
-
areas. This fellowship places a strong emphasis on the application of machine learning, artificial intelligence, and bioinformatics to solve complex biological problems. Potential research activities may
-
selection programs. Learning Objectives: By the end of this training/research experience, the fellow will be able to: Explain the structure and functional organization of the bovine genome and describe how
-
and BSL-4 laboratories utilizing a wide range of techniques such as in vitro and in vivo infection models, flow cytometry, ELISA, western blots, and multiplex immunoassays. Our projects rely