Research Scientist I
Apply NowCompany: Tulane University Staff
Location: New Orleans, LA 70119
Description:
Tulane University's Bywater Institute invites applications for a staff research scientist in the field of real-time data analytics to begin in 2022. The scholar will work with Bywater Institute Director Dr. John Sabo and interdisciplinary teams from across Tulane University in support of programs in Data-Driven and Computational Water Sustainability. This position supports and leads projects to develop data-driven decision support tools that assist our public and private sector partners in scoping, strategizing and designing corporate stewardship projects in large river basins across the world.
ESSENTIAL DUTIES: The successful candidate will work on big data analytics for surface and subsurface model and data integration. Much existing research on big data has focused on "big volume", which has spawned research and implementation on highly scalable, fault-tolerant data processing. There is a recent realization that big data systems should also be able to absorb and process high-volume incoming data in real time or with low latency so that timely information and insights can be derived for critical applications with real-time constraints. The candidate will investigate the design and optimization of big and fast data analytics systems as applied to collecting, storing and processing field data relevant to monitoring trends and underlying interdependencies in surface and underground water ecosystems across large geographical areas. Work will involve (a) benchmarking large complex spatial-temporal and networked data analytics workloads, (b) innovating in popular large scale data processing and analytics platform, such as Hadoop, Spark, and TensorFlow, with new algorithms for analysis of complex water ecosystems, and (c) optimization under multiple objectives including latency, throughput, and cloud computing cost.
Experience modeling and studying water resources
Excellent time management, interpersonal, organizational, and communication skills
Ability to write peer reviewed publications and present at public meetings
Ability to travel nationally and internationally up to 2 weeks per year
Applicants must have a Ph.D. in Computer Science with a background in high performance computing with strong and demonstrated interest in IoT, Machine Learning, Data integration, and Data Analytics. One or two research papers on related topics, as well as experience of implementation and experimentation with big data systems, are strongly preferred.Hands on experience with development of Web Apps, deployment and management of high performance and data-intensive compute clusters, running large experiments in those clusters, and development of advanced data management tools will be highly regarded by the screening committee.
ESSENTIAL DUTIES: The successful candidate will work on big data analytics for surface and subsurface model and data integration. Much existing research on big data has focused on "big volume", which has spawned research and implementation on highly scalable, fault-tolerant data processing. There is a recent realization that big data systems should also be able to absorb and process high-volume incoming data in real time or with low latency so that timely information and insights can be derived for critical applications with real-time constraints. The candidate will investigate the design and optimization of big and fast data analytics systems as applied to collecting, storing and processing field data relevant to monitoring trends and underlying interdependencies in surface and underground water ecosystems across large geographical areas. Work will involve (a) benchmarking large complex spatial-temporal and networked data analytics workloads, (b) innovating in popular large scale data processing and analytics platform, such as Hadoop, Spark, and TensorFlow, with new algorithms for analysis of complex water ecosystems, and (c) optimization under multiple objectives including latency, throughput, and cloud computing cost.
Experience modeling and studying water resources
Excellent time management, interpersonal, organizational, and communication skills
Ability to write peer reviewed publications and present at public meetings
Ability to travel nationally and internationally up to 2 weeks per year
Applicants must have a Ph.D. in Computer Science with a background in high performance computing with strong and demonstrated interest in IoT, Machine Learning, Data integration, and Data Analytics. One or two research papers on related topics, as well as experience of implementation and experimentation with big data systems, are strongly preferred.Hands on experience with development of Web Apps, deployment and management of high performance and data-intensive compute clusters, running large experiments in those clusters, and development of advanced data management tools will be highly regarded by the screening committee.