Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
single synthetic program of computational geometry. Specific interests include morphology, design topology, discrete differential geometry, packings, and machine learning methods for unstructured geometric
-
(yes, that means some museum and fieldwork!). Comparative analysis using advanced computational tools and wet lab techniques. Hands-on dissections of invertebrates for anatomical and physiological
-
, and embryology) and methods (histology and various types of microscopy, molecular biology, greenhouse studies). Please note: This is a two-year term appointment, with an end date two years from the date
-
Knowledge of standard research methods and statistical techniques, including multivariate regression and causal inference methods Attention to detail, organized, strong written and verbal communication skills
-
of Massachusetts would be a plus but not required. Attention to detail and professionalism are highly important for the role. Experience with participant recruitment and retention methods. CITI certified and trained
-
interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
-
single synthetic program of computational geometry. Specific interests include morphology, design topology, discrete differential geometry, packings, and machine learning methods for unstructured geometric
-
of the key criteria used when your application is evaluated. For projects that would be classified as basic research, we recommend applying for a Humboldt Research Fellowship. Should your programme search
-
for program evaluation. We study the properties of the method in a large-scale public program in India using satellite images. Role of the predoctoral fellow: The fellow will be implementing our statistical
-
particular long-term services and supports Experience programming in STATA Knowledge of standard research methods and statistical techniques, including multivariate regression and causal inference methods