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The United States Army Research Institute of Environmental Medicine (USARIEM) is offering a post-bachelor's-level fellowship in biomedical/mathematical modeling of humans exposed to extreme and austere environments
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) framework to assess biological risks associated with blast overpressure (BOP) from military weapon systems. You will engage in research and applied computational activities to model blast-induced energy
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have an interest in substance use, posttraumatic and/or operational stress, suicidality, and artificial intelligence/machine learning (AI/ML). What will I be doing and why should I apply? As the selected
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researchers in an effort to learn and perform structure-based protein design of vaccines and antibodies. Why should I apply? Under the guidance of a mentor, you will gain hands-on experience to complement your
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, public health, biostatistics, biomedical sciences, engineering, mathematics, statistics, or a related field. Experience or coursework involving artificial intelligence, machine learning, natural
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medical devices and systems using advanced technologies such as automation, artificial intelligence and machine learning, robotics, telemedicine, advanced displays, computer vision, and data-driven decision
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translational vaccinology within a highly collaborative research network. Within this opportunity, you will be engaged in the following learning objectives: Applying machine-learning/AI platforms including
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medical devices and systems using advanced technologies such as automation, artificial intelligence and machine learning, robotics, telemedicine, advanced displays, computer vision, and data-driven decision
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) extracellular vesicle manufacturing and characterization high content imaging biomaterials bioreactors multiomics (proteomics/metabolomics) immunology machine learning/AI single cell profiling Point of Contact
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research focuses on blunt, blast and accelerative injury and protection; crew survival in military helicopters and combat vehicles; the en route care environment; human operator health and performance in