Job opportunities at George Mason University and with the Energy and Resources Group (ERG) at the University of California, Berkeley

Thursday, October 1, 2015

Department chair
Computational and data sciences
George Mason University

The George Mason University, College of Science, Department of Computational and Data Sciences seeks applications for a senior scholar with significant administrative experience to serve as the chair of the Department of Computational and Data Sciences.

Responsibilities:
The individual serving in this position will be a leading scientist in a natural, computational, social science, or related discipline. The candidate should complement and enhance the expertise present in the program areas of the department which include data science, computational science, and computational social science. The chair is expected to foster an environment of teaching excellence, high research productivity, and distinguished service among the faculty.

Qualifications:
The successful candidate will have substantial teaching and research experience at the university level, and a history of successful faculty and student management. Applicants must have an earned doctorate and be eligible for appointment as a tenured associate or full professor. Other required qualifications include a substantial history of externally funded collaborative research projects; a distinguished publication record; an ongoing and impactful research program with evidence of mentorship of graduate students and junior faculty; and a record of effective teaching of courses in computational and data sciences across both undergraduate and graduate levels.

Further details: George Mason University job posting

Tenure-track assistant professor
Computational social science
George Mason University

The George Mason University Computational and Data Sciences (CDS) Department in the College of Science invites applicants for a full-time, tenure-track faculty position at the assistant professor level.

Responsibilities:
Beginning Fall 2016, this position is intended to primarily support the Computational Social Science (CSS) Program within CDS, including support of the PhD degree in CSS, a master’s degree in interdisciplinary studies, and a CSS certificate. This position will also support undergraduate programs that are currently under development.

Qualifications:
Potential for success in both research and teaching are the primary criteria for this position. Applicants should have a promising research record, with a deep knowledge of and interest in computation as applied to one or more of the social sciences. While we are open to expertise in all areas of computational social science, we are particularly interested in social network specialists interested in both theory and data. Applicants must have a PhD (expected completion by August 2016 is acceptable) from an accredited institution.

About the Program:
Methodologically, the CSS program focuses on data-driven social science models using social network and agent-based computational approaches from a complexity perspective. Current faculty members have domain expertise in economics and finance, political science and international relations, geography and geographic information systems, land use and cover change, and public policy. As one of the first programs of its type in the world, CSS has had significant success in both research and professional placement. Our students come from all over the world (the Americas, Europe, Africa, Asia and Australia) and have been placed at a variety of top universities (e.g., University of Oxford, University College London), at government agencies, as well as in the private sector, including start-up companies.

Further Information: George Mason University career opportunities

Assistant professor
Environmental science
Energy and Resources Group

The Energy and Resources Group (ERG) at the University of California, Berkeley invites applications for an assistant professor position in quantitative environmental science, with an expected start date of July 1, 2016.

ERG has a long and distinguished history of interdisciplinary research and teaching for a sustainable environment and an equitable society. Further information about ERG can be found at the Energy and Resources Group website.

Basic qualifications: The basic qualification for this position is completion of all PhD or equivalent degree requirements, except the dissertation, by time of application. Additional qualifications: Candidates must have a PhD or equivalent degree by the appointment start date.

Preferred qualifications: We are especially interested in candidates with quantitative expertise and interests in one or more of: global change science; toxics and pollutants; the environment-society interface; and ecology and biodiversity. The ideal candidate will have experience with some combination of: techniques for analysis of large data sets, mathematical modeling, methods in complex systems theory, and experimental and observational field methods. ERG especially encourages applicants with a strong interest in multiple scales of analysis from local to global. ERG is an interdisciplinary graduate program, so an ability to actively engage with colleagues from other disciplines such as social science and engineering is desirable, as is a compelling interest and engagement in public policy.

Training in multiple areas of the natural sciences (e.g., both physical and biological) is desirable.

Ideal candidates will have demonstrated potential for outstanding research and ongoing productivity. She or he will also have strong teaching and mentoring skills, or for those without an extensive background in teaching, a commitment to make this a core component of their professional portfolio. Teaching duties will include responsibility for a core ERG environmental science course, as well as development of more specialized seminars or courses, and participation in interdisciplinary seminars with other faculty.

ERG welcomes candidates who will bring to their research and teaching a perspective that comes from a non-traditional educational background or understanding of the experiences of those underrepresented in higher education. UC Berkeley is committed to addressing the family needs of faculty, including dual career couples and single parents.

Applications should include the following:

  • Cover letter
  • A recent curriculum vitae
  • A statement of research interests (up to three pages)
  • A statement of teaching interests and experience (up to two pages)
  • A description of quantitative training and the role of these skills in the candidate’s research, teaching and mentoring interests (up to one page)
  • Statement of contributions to equity and inclusion (Statement addressing past and/or potential contributions to equity and inclusion through research, teaching, and/or service.)
  • Copies of no more than three (article or chapter length) samples of relevant written work. At least one is required.
  • Three letters of recommendation

Each document should be submitted as a separate file. All letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e. dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letters.

For information about potential relocation to Berkeley, or career needs of accompanying partners and spouses, please visit the UC Berkeley Office for Faculty Equity & Welfare webpage. Follow this link to create an online application and submit the above materials no later than November 16, 2015.

Please direct questions to ERG group manager Megan Amaral at megana@berkeley.edu.

The University of California is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. See the complete University of California nondiscrimination and affirmative action policy (PDF).