Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
.•Cell-based virus assays [multi-color flow cytometry, primary cell culture (is an advantage)].•Experience in animal experimentation (FELASA B/C or equivalent) and in the development of transgenic and
-
: 281522554 Postdoctoral Research Associate D-26-ENE-00004 | Research | Andlinger Center for Energy and the Environment The Peng group at the Andlinger Center for Energy and the Environment and the School
-
they can participate dynamically in multi-energy markets at both building and district scale. You will develop high-fidelity techno-economic models of chillers, heat pumps and thermal energy storage
-
Post Doctoral Fellow - Biostatistics and Data Science - (2500018O) POSTDOCTORAL FELLOW: The Maryland Psychiatric Research Center (MPRC) at the University of Maryland School of Medicine is
-
will include an important component of code development, in order to produce multi-color light curves of supernovae in 1D simulations that account for the physics of the stellar core (nucleosynthesis and
-
-and-biosystems/bioprocess-engineering-0 ). The research group closely associates with the Bioinnovation Center ( https://www.aalto.fi/en/aalto-university-bioinnovation-center ), funded by Jane and
-
Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest biotechnology in Northern Sweden. Our mission is to perform excellent and
-
application of cumulative impact assessment model using food webs, which is intended to assess impact of multi-stressors on trophic and non-trophic interactions networks. The modelling will be primarily based
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
predictive models for complex multi-physics dynamical systems as well as towards designing observer-based state estimators from output timeseries data measurements. The research also involves development
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable predictive models for complex multi-physics dynamical