Engineering Tools to Untangle Learning and Memory
|Interdisciplinary Areas:||Engineering and Healthcare/Medicine/Biology
Learning and short-term memory is driven by dynamic variations in the connective strength of neurons in the hippocampus. Underlying these plastic changes is a complex network of protein signaling that is itself regulated and rapidly varying in time and space. Disruptions in these networks leads to neurological disorders such as autism, Parkinson’s disease, Alzheimer’s disease and other disorders that affect millions of people. New advances in computational power, super resolution microcopy, and molecular detection are allowing scientists to describe these highly dynamic systems at resolutions and with quantitative detail not previously possible. Our team of engineers and scientists seek a multidiscipline-minded postdoctoral scholar to lead the vision of applying computational biology, molecular neuroscience, and super-resolution imaging to describe fundamental processes in neuronal connectivity. These advances will be applied to quantify the relative effects of key protein interactions so that therapies can be specifically tailored to address disruptions and dysfunctions that lead to complex learning and memory disorders.
The ideal candidate would have a background in chemical engineering, biomedical engineering, biophysics, biochemistry or related fields. Experience in protein assay development, protein expression and purification, or protein kinetics is desired. The successful candidate will demonstrate depth in quantitative reasoning and multidisciplinary approaches, and be an excellent communicatory and team player.
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