13 phd-in-architecture-and-built-environment Postdoctoral positions at Harvard University
Sort by
Refine Your Search
-
the pseudostratified architecture found in epithelial tissues, and how the architecture is exploited for various functions such as morphogenesis, organ development, and tissue fate. We use diverse model organisms
-
and engineering staff on computing architecture, including networking, data pipeline design and storage; data analysis and data collection software; and machine learning research Collaborate with other
-
life-and-death struggle against lethal stresses in their microscopic world. We study how microbes adapt to their ever-changing environment, using simple and complex survival strategies. We hope to deeply
-
research and/or clinical doctorate (for example, PhD, MD, DO, DC, ND, DDS, DMD, DVM, VMD, ScD, DNS, PharmD or equivalent doctoral degrees). There is no citizenship requirement for K99 applicants
-
programs, including MD and/or PhD programs, as well as industry positions. Responsibilities will be: Mouse husbandry, genotyping, dissection Molecular biology, e.g. Western blotting, cloning Cyclic
-
year, renewable if additional funding resources are secured. Basic Qualifications The successful applicant should have PhD in Linguistics, and extensive research experience on some of the following
-
of the rich and varied training and career development opportunities offered at HSPH. Basic Qualifications · PhD or equivalent in computational biology, computer science, epidemiology, statistics, mathematics
-
, 120-128. Basic Qualifications A PhD (or equivalent), or near completion, in a relevant field such as chemistry, physics, materials science, or engineering (chemical, electrical, or mechanical
-
strong research program in astrophysics and provides a stimulating environment. Women and minorities are strongly encouraged to apply. AAE/EOE. Special Instructions Letters of reference should be submitted
-
computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI environments and tools. Prior experience