[ES_JOBS_NET] Postdoc position at UC Berkeley

[Lindsey Heagy]

Hello All,

Please see below for details on a Postdoc Position with Dr. Fernando Pérez
in the department of Statistics at UC Berkeley.

All the best,
Lindsey

-----------
Postdoctoral Researcher: Data Science, Earth Science with a Cryosphere
emphasis and Open Source Software

Supervisor: Dr. Fernando Pérez <http://fperez.org>, UC Berkeley Department
of Statistics <https://statistics.berkeley.edu/people/fernando-perez>.

Job Description:

I am looking for a post-doctoral researcher interested in the intersection
of geoscience (with a particular emphasis on cryosphere science and
glaciology), data science, and open source computational tools to join our
group in the Department of Statistics at UC Berkeley. You would be joining
a multi-disciplinary team of researchers with backgrounds in statistics and
geoscience as well as folks leading open-source projects in the Jupyter
community. To give you a flavor of a few projects that we have on the go:


   -

   Jupyter meets the earth
   <https://blog.jupyter.org/jupyter-meets-the-earth-1b0eb33c83f>: we are
   using research avenues in climate science, hydrology, geophysics and
   cryosphere science to motivate technical developments within the Jupyter
   ecosystem. We are aiming to strengthen the cryosphere science uses of these
   tools, including a partnership with the team at the University of
   Washington that leads the development of the IceSat-2 HackWeeks
   <https://icesat-2hackweek.github.io>. We aim to jointly contribute to
   the cryosphere science community by providing better tools for large-scale
   data-driven research in an interdisciplinary setting, and to inform the
   evolution of Jupyter thanks to these concrete use cases in scientific
   research, education and collaboration.



   -

   Glaciology / cryosphere science: This is a current focus of several of
   the graduate students working with me and is an area I am very interested
   in making contributions to. In addition to the above, we are connected with
   collaborators at the University of Washington on a project to develop
   software for working with ICESat2 data (icepyx
   <https://github.com/icesat2py/icepyx>). We are also initiating
   collaborations with colleagues at the School of Mines to look at machine
   learning approaches for estimating surface-water volumes through time on
   Greenland and Antarctica. We would welcome contributions to these projects
   as well as new ideas or other avenues of research in the cryosciences.



   -

   Physics & Machine Learning: I am interested in questions that are at the
   intersection of physically-driven models and statistical learning. This is
   a general theme throughout the projects we are pursuing, and I would
   welcome the opportunity to work with someone who is interested in this
   intersection, especially as these ideas are expressed in geoscience
   applications.


An ideal candidate would

   -

   Have a PhD in a field such as (Geo)Physics, Earth and Planetary Science,
   Statistics, Data Science or related.
   -

   Have experience and interest in mentoring PhD students in the group.
   -

   Have demonstrated leadership in collaborative projects.
   -

   Be self-directed on broadly-scoped projects.
   -

   Be proficient in Python or R and tools in the open-source data science
   ecosystem.
   -

   Be willing to contribute to grant proposal writing.


Location-wise it is preferable if the candidate can work locally at
Berkeley, but I am open to considering remote options, especially at the
start (and given the coronavirus uncertainty, that may even be required at
least for a while).

If you are interested, please provide:

   -

   A Curriculum Vitæ
   -

   And a short (1-2 page) statement describing your research interests and
   how you envision contributing to the projects described above


By email to Fernando Pérez and Lindsey Heagy (fernando.perez at berkeley.edu,
lheagy at berkeley.edu).
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