Data Science Scholar via AGU

Arizona State University

Tempe, AZ, United States 🇺🇸

Arizona State University’s Future H2O invites applications for 1 postdoctoral scholar in the field of big/fast data analytics to begin in 2017. The scholars will work with Dr. Dragan Boscovic in ASU’s Center for Assured and Scalable Data Engineering (CASCADE) and Future H2O director Dr. John Sabo, ASU’s Decision Theater and faculty members in ASU’s Ira A. Fulton Schools of Engineering and School of Earth and Space Exploration and contribute to Future H2Os program area in Data-Driven and Computational Water Sustainability.  This program area aims 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.   Applicants must be within four (4) years of receipt of a Ph.D. degree at the time of application.

Essential duties

The successful postdoc will work on big and fast data analytics for surface and subsurface model and data integration.  Much existing research on big data has focused on “big volume”, which has spawn research and implementation on highly scalable, fault-tolerant data processing. There is a recent realization that big data systems should also be able to support “big velocity”, that is, 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 applications. This project aims to 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. The project will involve (a) benchmarking large complex analytics workloads, (b) innovating in popular big data systems, such as Hadoop or Spark, with new algorithms for analysis of complex water ecosystems, and (c) optimization under multiple objectives including latency, throughput, and cloud computing cost.

Minimum qualifications

Applicants must have a Ph.D. in Computer Science with a background in distributed computing with strong and demonstrated interest in IoT 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.

Desired qualifications

Hands on experience with development of Web Apps, deployment and management of  Hadoop and Spark clusters, running large experiments in those clusters, and development of advanced data management tools will be highly regarded by the screening committee.

Instructions to Apply

To review and apply for this position, please email application materials to [email protected]. Applicants must submit:

  1. Cover letter explaining how prior experience and qualifications are appropriate to the job activities.
  2. Statement of research accomplishments. Applicants should describe experience and goals related to the program, highlighting strengths of the applicant’s experience. Applicants are encouraged to demonstrate their dedication to solving sustainability problems through research and scholarship, capacity to work effectively in interdisciplinary teams, and excellent communication skills. Special emphasis will be placed on candidates who explain how their research would both benefit from and advance ongoing activities in the area of public-private partnerships to solve sustainability problems, who strongly integrate the pursuit of knowledge about earth science and modelling with end users outside of the ivory tower.
  3. Curriculum Vitae or resume.
  4. Letters of recommendation. Provide the name, phone number, address, and e-mail address of three references.

Only electronic applications will be accepted.

Application Close Date

The deadline will be January 22, 2018 at 11:59pm Eastern time.

Department Information

Future H2O is ASU’s umbrella water research initiative, housed in Knowledge Enterprise Development.  For more information see:  Follow us on Twitter: @FutureH2O.