Faculty Positions - Computational Science and Data Analytics

Colorado School of Mines
Golden, Colorado (US)
Nov 24, 2020
Dec 24, 2020
Career Level
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Relocation Cost
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Aligned with the Colorado School of Mines (Mines) emphasis on Earth, Energy and Environment, the institution is focused on addressing major societal challenges at the intersection of its traditionally strong disciplinary tracks. To strengthen these efforts, Mines has initiated a search to recruit highly talented interdisciplinary faculty.

We invite applications from candidates with expertise in broad disciplinary areas associated with the fields of Computational Science and Data Analytics. Candidates who have demonstrated the potential for conducting high impact research and teaching are highly desired. The successful candidates will be placed in various departments across campus where they best fit for teaching and research synergies, and joint appointments will be considered as appropriate.

Specific interests for this cluster include positions in:

  • Computational Mathematics and Data Science Methods with particular interest in algorithm analysis and development, high performance computing, and applications to scientific and engineering modeling as well as statistical and machine learning and data analysis.
  • Business Analytics with particular interest in Business/Data Analytics, Management Science, Operations Research, Industrial Engineering, or a closely related data-analytics discipline to develop and support the quantitative business programs on campus.
  • Applied Data Science and Machine Learning with particular interest in data science, data analytics, geostatistics, machine learning and other artificial intelligence techniques to address earth and environmental science problems of societal relevance.
  • Computational Hydrology with particular interest in surface water hydrology, groundwater hydrology, hydrogeophysics, “big data” hydrology, or large-scale modeling of hydrologic systems.

More details about the positions can be found HERE.

Anticipated home departments include, but are not limited to Applied Mathematics and Statistics, Civil and Environmental Engineering, Computer Science, Economics and Business, Geology and Geological Engineering, Geophysics, Mining Engineering, and Petroleum Engineering.

For further information, please contact the search chair, Prof. Kamini Singha at ksingha@mines.edu.

Minimum Qualification:

  • Ph.D. in a related discipline from an accredited program by the time the appointment begins.
  • Strong interpersonal and communication skills.
  • Commitment to excellence in teaching and curriculum development at both the undergraduate and graduate levels.
  • Assistant Professor candidates must possess academic, research lab and/or industry experience and accomplishments in a related field.
  • Associate and Full Professor candidates should have similar credentials as Assistant Professor candidates as well as national distinction and a substantial record in research, teaching and/or service. In addition, Full Professor candidates should have an established international reputation.

Preferred Qualification:

  • Successful record of teaching and research obtained via academic research, college-level teaching and/or industry or national lab experience.
  • Commitment to diversity, inclusion and accessibility.
  • Demonstrated success in securing externally funded grants and contracts for those applying at the rank of Associate Professor or Professor.
  • Demonstrated record of research publications in archival journals and conference proceedings.

Apply Here: https://www.click2apply.net/xWj1BEIkmKrRue8EfxkWj