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|JOB title=PhD Student Opportunity in Water Quality and Machine Learning | |JOB title=PhD Student Opportunity in Water Quality and Machine Learning | ||
|JOB position=1 PhD Position | |JOB position=1 PhD Position | ||
|JOB CSDMS yes no= | |JOB CSDMS yes no=No | ||
|JOB department=Civil and Environmental Engineering | |JOB department=Civil and Environmental Engineering | ||
|JOB university=Florida State University | |JOB university=Florida State University |
Latest revision as of 09:54, 18 November 2021
PhD Student Opportunity in Water Quality and Machine Learning
Florida State University, Florida, United States
Start reviewing process: 3 January 2022
Start reviewing process: 3 January 2022
Posting:
Position: 1 PhD Position
Start reviewing process: 3 January 2022
Apply online:
See attached file:
|
I am recruiting one PhD student to join my group in the Civil and Environmental Engineering (CEE) Department at Florida A&M University (FAMU)—Florida State University (FSU) College of Engineering as a graduate research assistant beginning Spring 2022. The student will receive stipend, full tuition waive and benefits.
REQUIRED/DESIRED QUALIFICATIONS AND SKILLS · A degree in engineering (civil, agricultural, water resources or environmental), sciences (environmental, earth or computer) or any closely related field · Understanding of hydro-biogeochemical processes in coupled inland-estuary systems · Strong analytical and quantitative skills · Computer programming (R, MATLAB or Python), data management, watershed modeling, Machine Learning techniques, water quality modeling, time series analyses and geospatial analyses (e.g., GIS) · Independency, communication, presentation (oral and written), fast learning and the ability to work in an interdisciplinary team and with a group of stakeholders
Highly motivated applicants should contact Dr. Ebrahim Ahmadisharaf (eahmadisharaf@eng.famu.fsu.edu) with their CV, unofficial transcripts, copy of English test scores (for non-English speaking applicants) and a brief statement describing how their interests connect to this research project. See the attachment for details.Of interest for: Terrestrial Working Group Coastal Working Group Hydrology Focus Research Group Artificial Intelligence & Machine Learning Initiative Modeling Platform Interoperability Initiative River Network Modeling Initiative