Arizona State University
Center for Assured and Scalable Data Engineering (CASCADE)

Arizona State University’s Center for Assured and Scalable Data Engineering (CASCADE) invites applications for a post-doctoral researcher in data management, data analytics, and machine learning to begin in 2022. The scholar will work with CASCADE Director Prof. K. Selcuk Candan, Prof. Huan Liu, and a multi-university, multi-disciplinary team within the context of a project on Data-Driven Water Sustainability. This position supports and leads research in data-driven decision support technologies that will assist partners in scoping, strategizing, and designing sustainability efforts across the Nation.

Essential duties —————-

The candidate will, therefore, investigate the design and optimization of data- and model-integration and analytics systems as applied to collecting, storing, and processing data relevant to monitoring underlying interdependencies in water ecosystems. Developing situational understanding and the ability to make informed forecasts is critical to operating effectively, efficiently, safely, and securely in human-centered environments. Yet, because of the size and complexity of the data and the varying spatial and temporal scales at which the key processes operate, experts often lack the means to understand and predict relevant processes to support robust decision making. Development of big data tools and services to enable communities that are resilient, self-sustaining, and livable necessitates (a) system-wide data and model gathering and integration, (b) spatio-temporal and causal analytics, and (c) physical and behavioral modeling and large scale simulations. Work will, therefore, involve research into big data and model integration, causal learning and discovery, large scale data- and model-driven simulations, emulations, and forecasting, and data-driven and model centric operational recommendations.

Minimum qualifications —————-

Applicants must have a Ph.D. in Computer Science and Engineering or a related field with background in Data Integration, Data Analytics, or Machine Learning. Demonstrated excellence on related topics, as well as experience of implementation and experimentation with big data and decision support systems, are required.

Desired qualifications —————-

Hands on experience with development of deployment and management of high performance and data-intensive compute clusters, running large experiments and simulations on those clusters, and development of advanced data management tools will be highly regarded by the screening committee.

Instructions to Apply —————-

Evaluation of the applications will start immediately and will continue until the position is filled. Only electronic applications will be accepted. Applicants must submit, by email to candan@asu.edu and huan.liu@asu.edu, the following:

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 research, highlighting strengths of the applicant’s experience. Applicants are encouraged to demonstrate their dedication to solving real world 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 to solve sustainability problems.
3. Curriculum Vitae or resume.
4. Letters of recommendation. Provide the name, phone number, address, and e-mail address of three references.

Please include the prefix “[DI/ML Application]” in the subject line of your email.