Sort by
Refine Your Search
-
breeding and molecular biology. Learning Objectives: As a result of this experience, the participant will: Learn methods to conduct transformation of sugarcane, Learn genomics, bioinformatic methods
-
, pharmacovigilance, pharmacoepidemiology methods development). In general you will have opportunities to learn: Understanding of pharmacovigilance workflows; GenAI based algorithm and agent development for causality
-
of basic laboratory assays (i.e. ELISA, flow cytometry, western blots, cell culture or other molecular and cellular biology methods), immunological/virological assays (i.e. neutralization assays, plaque
-
the ORISE Research Participation Program at the U.S. Department of Defense . Qualifications The qualified candidate be a current faculty member at an institution of higher education and will have a PhD
-
, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
-
of honey bee samples using microbiological, molecular biological, and chemical methods. This includes characterizing and quantification of pathogens and beneficial microbes, which are critical components
-
on developing methods for the genetic engineering of grapevine (Vitis vinifera) and potentially other plants with the goal of generating plant varieties with novel desirable traits. Combinations of tissue culture
-
agricultural yield prediction models for use in plant breeding through a combination of high-throughput phenotyping data, physiological crop growth modeling, and artificial intelligence methods. There will be
-
, diafiltration and protein precipitation Set up, develop and optimize protein purification methods using chromatography equipment Purify protein samples using immunoaffinity, metal affinity, size exclusion, and/or
-
, the participant will: (1) gain experience in computational modeling to optimize manufacturing high-purity reactive refractory metal powders, (2) learn advanced modeling methods based on density functional theory