Postdoctoral Position in NY: Molecular and Coarse-Grained Models of Polymers, Drugs, Membranes, Proteins
The Department of Chemistry at City University of New York (CUNY)-College
of Staten Island seeks a postdoctoral associate with interdisciplinary training
to conduct computational-based research within the research group of
Dr. Sharon Loverde. The work will be interdisciplinary covering molecular
self-assembly, coarse-grained model development, hydrophobic drug solubility in polymers and membranes, and protein-membrane interactions.
Applicants must have a Ph.D. in chemistry, physics, egineering, pharmacology, or a related field. Applicants should have experience with common molecular simulation techniques (molecular dynamics, Monte Carlo) in a Linux environment.
Experience in TCL scripting and familiarity with LAMMPS, NAMD, VMD, HOOMD-blue would be a significant advantage, but is not required. Additionally, experience working with mixed CPU/GPU or GPU based molecular dynamics codes are a plus, as well as experience with NSF XSEDE computational resources.
City University of New York-College of Staten Island is located in southwest
New York City, easily accessible to Manhattan, Brooklyn, and the other boroughs of NYC. Additionally, College of Staten Island is home to a rapidly growing
High Performance Computing facility (http://www.csi.cuny.edu/cunyhpc/).
The position is available for a one year contract initially, and extendable
for up to two years, dependent on mutual agreement. For this position, the
successful candidate will be able to communicate effectively in both written
and spoken English.
Please send a letter describing your research interests and expertise, along
with a curriculum vitae in PDF format via email, to Prof. Sharon Loverde:
sharon.loverde@csi.cuny.edu
https://sites.google.com/site/loverdelaboratory/home
Computational Science Postdoctoral Fellowship - 75275
Organization: CR-Computational Research
The Scientific Computing Group in the Computational Research Division at
Lawrence Berkeley National Laboratory has an immediate postdoctoral
fellow opening in the area of development and applications of computational
algorithms enabling discovery and characterization of functional electronic
materials.
SPECIFIC RESPONSIBILITIES:
The successful candidate will participate in research activities focused on
development and applications of novel algorithms, approaches and software
in the area of material informatics. Of particular interest is the development
of capabilities 1) enabling enumeration, generation and characterization of
defects in crystals, as well as 2) enabling automatic structure analysis and
structural descriptor generation for efficient materials screening as well as
data mining. The successful candidate will help to integrate the developed
software into the Materials Project (http://www.materialsproject.org/),
enabling users worldwide to efficiently discover and characterize diverse
electronic materials. This person will be placed in a Scientific Computing
Group team led by Dr. Maciej Haranczyk and will collaborate with researchers
of the recently funded DOE BES Center for Functional Electronic Materials, in
particular, the groups of Prof. Mark Asta (UC Berkeley) and Dr. Kristin Persson (LBNL).
KEY SUCCESS FACTORS:
- Ph.D. in Cheminformatics/Material Informatics, Computational
Chemistry/Material Science, Computer Science, Applied Mathematics or a
related field within the last three years, with a strong background in
programming.
- A knowledge of crystal structure analysis (involving group theory, analysis
of symmetry, defects and topology of periodic structures) is highly desirable.
- Experience in cheminformatics/material informatics techniques (structure
enumeration, QSPR, data mining) as well as material modeling techniques is a plus.
- The successful candidate should be able to program proficiently in C/C++
and Python.
- Excellent communication skills and being able to work independently are
essential.
KEY SKILLS:
Scientific computing, Cheminformatics/Material informatics, Programming
(C/C++ and Python)
Equal Employment Opportunity: Berkeley Lab is an affirmative action/equal
opportunity employer committed to the development of a diverse workforce.
Apply directly online at http://bit.ly/lbl75275CCL and follow the on-line
instructions to complete the application process.
