Jobs board
This is an informal listing of Positions attendees have available in their organizations.
USDA Research Ecologist
Permanent , Las Cruces, NM
Summary
The mission of the Research Unit is to develop and transfer science-based approaches for sustainability of agriculture and other land uses in rangelands of the Western U.S. This research is a component of ARS National Program 216 Agricultural System Competitiveness and Sustainability. The incumbent’s assigned area of research is to develop new knowledge of ecosystem and landscape processes that enable the prediction of landscape change in rangelands and other agroecosystems. Duties are: 1)Conduct studies of ecosystem, soil, and landscape processes using field studies, process models, and/or spatial models that enable landscape to regional-level predictions of ecosystem and land cover change in drylands.
Responsibilities
Integrate research to develop spatially-explicit forecasts of ecosystem responses to management and climatic drivers, particularly in rangelands but also with respect to cropland and urban land uses in drylands. 2) Utilize spatially-explicit information for collaborative conservation and management efforts (e.g., resilience-based management, sustainable intensification), including those of agency programs and stakeholder-led organizations. 3) Oversee the production and use of information via experiments synthesis, and models featuring and long-term data on climate, vegetation, soils, and soil water dynamics in drylands. 4) Developing and transferring information products to land managers and other stakeholders.
https://www.usajobs.gov/GetJob/ViewDetails/543241500.
Deadline: 09/06/2019
USDA Postdoc, Mass Spec and Machine learning
Two years, Gainesville, FL
Summary
The USDA Agricultural Research Service, Center for Medical, Agricultural, and Veterinary Entomology (CMAVE) will soon have an opening for a postdoctoral research associate. The project primarily involves developing volatiles-based mass spectrometry and machine learning technology to dramatically improve animal welfare in the egg industry.
About 700 million chicks are hatched annually in the US egg industry. Half of those are male and they are culled the day they hatch because they lack economic value. We are developing a method to determine the sex of the egg when it is laid. Our novel approach uses non-invasive, high-throughput volatile compound mass spectrometry and machine learning. This will allow the male eggs to be diverted and used for food products before the chick develops the ability to sense pain. Early sex identification also reduces industry costs by reducing the need for egg incubators and labor. The postdoc in this position will build off the existing work and intellectual property of the group to quickly create a viable commercial prototype in 18 to 24 months. The position requires someone with good experience in any field of mass spectrometry. Additional knowledge in analytical chemistry, chemical ecology, poultry, or statistics is a plus. An ideal candidate will also have a collaborative, inventive and entrepreneurial spirit, a problem-solving mentality, and an interest in gaining valuable skills in machine learning.
For more information contact adam.rivers@usda.gov. https://tinyecology.com
USDA Postdoc, Salmonella detection and characterization with machine Learning
Four years, Gainesville, FL
Summary
The USDA Agricultural Research Service, Center for Medical, Agricultural, and Veterinary Entomology (CMAVE) will soon have an opening for a postdoctoral research associate to work on a project entitled “Salmonella Typing And Phenotypic Prediction From Genomes And Metagenomes Using Population Genomics And Machine Learning.”
Salmonellosis sickens 1 million people and has an estimated economic impact of $3-11 billion annually in the United Sates. Salmonella is tracked in both outbreak situations and as part of the routine monitoring of animal production and processing facilities. Key public health and food safety agencies in the US are in the midst of transitioning to whole genome sequencing for all isolates entered in the Pulsenet database. Unfortunately, public health agencies face a challenge from the increased use of culture independent diagnostic tests (CIDT) which don’t provide public health laboratories with isolates that can be typed to track outbreaks. Metagenomics has the potential to address the challenge of CIDT and to cut the time to identify a strain from 4 days to 1 or 2, but current methods for molecular typing like whole genome multi locus sequence typing (wgMLST) do not work on fragmented metagenomic data. The USDA Food Safety Inspection Service, does not face the challenge of CIDT but they need better information on antibiotic resistance and sanitizer resistance in production facilities. We are developing software that rapidly predicts wgMLST, serotype, identifies closely related strains and predicts the resistance to sanitizers and antibiotics from genomes or metagenomes. This software is novel in its application of SNP analysis to pathogen typing, its use of autoencoders to represent sequence data and its application of deep learning to predict antimicrobial and sanitizer resistance.
For more information contact adam.rivers@usda.gov. https://tinyecology.com
UF/USDA Postdoc
Up to 3 years, Gainesville, FL
Summary
This position will focus on developing probabilistic graphical methods like Bayesian networks to integrate metagenomic and metabolomics data. This work has a larger goal of of developing methods to rationally engineer microbial consortia.
For more information contact adam.rivers@usda.gov. https://tinyecology.com