Resources for Graduate Students and Postdoctoral Fellows
The training and mentorship of younger and early career mathematicians is a special focus of the institute.
Professional development round-table discussions are scheduled throughout ICERM's semester programs. These discussions are intended for postdocs and graduate students from ICERM, Applied Mathematics, Computer Science, and Mathematics departments at Brown University. Sessions are led by Brown faculty and ICERM long-term visitors.
During semester programs, there are regularly scheduled postdoc-graduate student seminars, expressly limited to junior researchers. This gives participating postdocs and graduate students an opportunity to discuss research topics and any other issues openly, without senior people present. The format is completely flexible. For example, it could feature talks by postdocs or graduate students on their current research, or provide an opportunity to read and report on papers, or give an introduction to upcoming talks in other seminars. The group could even ask a senior participant to give a tutorial lecture and then follow up with a discussion session afterwards.
A mentor matching program is in place for those graduate students and postdocs who are at ICERM long-term without their advisor. An ICERM director works closely with the program organizers and the visitors' advisors to make an appropriate mentor/mentee match.
At the beginning of each semester program, ICERM hosts mentor/mentee introductory meetings. These meetings emphasize the idea that mentors should help mentees start to build a research cohort within a field, and help them create contacts and resources which will persist beyond the program and are important for their professional development. ICERM provides a set of ideas and guidelines for these meetings for mentees and mentors .
Location: Schlumberger Doll Research (SDR), Cambridge, MA, USA
Fundamental and applied research projects are carried out in Schlumberger Doll Research (SDR) to develop new technologies for application in the oilfield. The Mathematics and Modeling Department is investigating the development and application of state of the art data science methods to measurement data pertaining to complex problems in the development of oilfields.
The intern will work with a senior scientist or within a team of scientists and domain experts to develop and implement new applications of machine learning and/or interpretation frameworks such as probabilistic graphical modeling.
The successful summer intern has a reasonably good background in data science and associated domains such as signal processing, probability and statistics, machine learning, reasoning and inference frameworks. Familiarity with machine learning platforms such as TensorFlow or Theano, etc, is preferred.
Advanced undergraduate or graduate (MS/PhD) student in electrical engineering, computer science, artificial intelligence, physics, or related fields with course work and preferably thesis work related to the subject domain.
About Schlumberger-Doll Research
Schlumberger-Doll Research (SDR) is the prime corporate research center for Schlumberger, the world’s leading supplier of technology, integrated project management and information solutions to customers working in the oil and gas industry worldwide. SDR hosts more than 110 scientists working in various fields including geophysical measurements, geosciences, and computational sciences. SDR is located within the MIT campus at minutes walking from many landmark building such as CSAIL, Stata center. Several dozen interns are hosted each summer at SDR. Previous interns have highlighted the working environment, camaraderie, diversity in expertise and domains of interest, learning about new technical challenges, and the cafeteria as prime elements they enjoyed during their stay at SDR.
Applicants should send a brief letter of intent and resume via E-mail to SDRJobs@slb.com with the reference MM-SZ.
Schlumberger is an equal opportunity employer and is committed to the diversity of its workforce.
Brown Horizons Seminar:
Horizons is a seminar organized by members of the Brown University math department with the following goals: to discuss issues of gender, racial, and sexual inclusivity in STEM fields; to provide career advancement and job placement advice to graduate students; and to promote the research and work of traditionally under-represented mathematicians by hosting several colloquium-style mathematics talks. Details can be found at: https://www.math.brown.edu/~sswatson/horizons.html.
ICERM will hold informal round-table discussions for postdocs and graduate students from ICERM and the applied mathematics, computer science, and mathematics departments
with Brown faculty and ICERM long‐term visitors. All meetings will take place from 9:30‐10:30am in ICERM’s lecture hall (room 1115) on the 11th floor of 121 South Main Street.
Sessions marked “mandatory” are mandatory for NSF supported participants and replace Brown’s BEARCORE training. A more detailed description of the topics to be discussed can
be found in
the Spring 2017 schedule.
- Job listings:
- Academic and nonacademic job searches:
- Resources and links at Brown:
- CareerLAB: The CareerLAB website links to an extensive doctoral student packet with information about PhD work and the application process and materials for the academic and nonacademic job market. The CareerLAB also offers workshops and individual consultations on resume and cover-letter writing
- Sheridan Center: Contains information about cover letters, teaching statements, interviews, and negotiations
- Brown Student Job and Internship Board: Contains also job postings for graduate students
- Components of applications for the academic job market:
- Joint Mathematics Meetings:
- Some Hints on Mathematical Style written by David Goss
- How to write effective manuscript reviews written by David Brainard
- MAA grant-writing guide
- Professional Ethics: Taking the High Road written by Dianne O'Leary (published in SIAM News Volume 44, Number 8, October 2011)
- NSF's Broader Impacts Criterion
- Funding agencies:
- National Science Foundation (NSF)
- Other Funding Agencies: