19 parallel-computing-numerical-methods "DIFFER" Postdoctoral positions at Cornell University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
Postdoctoral Associate – MEMS/NEMS Fabrication and Characterization for Piezoelectric/Ferroelectric Devices and Emerging Computing Hardware The SonicMEMS Laboratory at Cornell University is
-
autonomy. The postdoctoral associate will be expected to work both collaboratively and independently on research projects, advancing computational methods using machine learning, developing automated
-
research project in any of several areas relevant to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic
-
, including machine-learning methods, that improve the identification or enumeration of overlapping vocal individuals. Array localization, spatially explicit capture-recapture, distance sampling, or other
-
methods to quantify and propagate uncertainty across integrated monitoring frameworks Developing methods for joint occupancy estimation using eBird and acoustic detections Developing approaches for
-
. We are especially excited to hear from candidates eager to invent new tools, wetlab approaches for circulating nucleic acids, interpretable machine learning for biomarker discovery, and methods we
-
limited to, quantum materials and their synthesis; quantum sensing and measurement, including the development of new probes and instrumentation; quantum devices and computing; and quantum systems based
-
engineering education, and research method innovation. The collaborative expertise of the postdoctoral associate cohort, using both qualitative and quantitative methods, will contribute to, for example
-
crosses the boundaries of theory and practice, who is invested in innovative and experimental research methods and creative practices, and who brings these methods into the classroom. The successful
-
with life cycle assessment methods and software, including uncertainty methods, spatialized approaches, and integration with dynamic modeling frameworks. Experience applying or developing mechanistic