53 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Pennsylvania State University
Sort by
Refine Your Search
-
) develop and apply statistical genomic methods to analyze multi-omics datasets for understanding complex disease etiology and (2) develop and apply novel statistical models to analyze EHR data
-
IAQ. Designing and conducting energy, IAQ, and economic simulations of novel control systems. Aggregating, synthesizing, and interpreting HVAC system data from field sites. Developing data-driven models
-
). Additional experience and training in basic microbiology techniques and preclinical mouse models, including gnotobiotic mice, are desirable but not required. Excellent oral and written communication skills, as
-
, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant
-
thermophoresis, and animal models of Alzheimer's disease to study the mitochondria-mediated cell death mechanisms in Alzheimer’s disease pathogenesis. The candidate will be involved in large-scale protein
-
. Education and Experience: The position requires a Ph.D. in Biology, Ecology, Evolution, Entomology, Virology, Molecular Biology, or a related field. Competence with statistical software and data management
-
to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning – in both neurotypical people and people with aphasia. The successful candidate will have a PhD in a relevant
-
functional magnetic resonance imaging: fMRI) methods to investigate iconicity in spoken language – the idea that the sound of a word may convey its meaning. The successful candidate will have a PhD in a
-
resonance spectroscopy applied to investigate post-translational modifications of intrinsically disordered proteins. The position requires a PhD in chemistry with a focus on spectroscopy applied
-
for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine