[Job-offers-cs] Two postdoctoral research associate positions at Los Alamos National Laboratory

[Pekka Orponen]

Come join one of the most innovative and creative multidisciplinary 
research institutions!

The Information Sciences Group (CCS-3) in the Computer, Computational 
and Statistical Sciences Division at Los Alamos National Laboratory 
(LANL), in collaboration with the Physics and Chemistry of Materials 
Group (T-1) and Theoretical Biology and Biophysics Group (T-6) in the 
Theoretical Division, are recruiting a highly motivated post-doctoral 
research associate. We have secure funds for supporting two 2-year 
postdoctoral research associates focusing on

  * (IRC92672) Multiscale modeling for Discrete Dislocation Dynamics:
    The successful candidate will be part of a multi-divisional team
    working on the development of an integrated and automated multiscale
    simulation capability, driven by exascale computing, data-driven
    methods including but not limited to machine learning and rigorous
    uncertainty quantification. The successful candidate will be
    expected to work in an interdisciplinary team environment and
    interact with scientists working in material science, data science,
    statistical physics, machine learning, in different organizations of
    the Laboratory (CCS-3/T-1/CCS-7). The candidate will develop and
    implement data-driven and dynamical coarse-graining methods for
    upscaling/construction of mesoscopic models that are capable of
    capturing long-time behavior using atomistic simulation data. The
    candidate will also develop integrated uncertainty quantification
    methods for dynamically downscaling/folding back to atomistic
    simulations when the quality of mesoscopic models deteriorates in
    the dynamical simulations.


  * (IRC88412) The successful candidate will develop and implement
    cutting-edge statistical inference methods and apply them to
    biological data, with an emphasis on applications in epidemiological
    forecasting. The fundamental research will involve the development
    of efficient and robust methods for high-dimensional computational
    Bayesian analysis, leveraging both adjoint sensitivity methods and
    neural computation. The successful candidate will be expected to
    work within an interdisciplinary team environment and interact with
    scientists working in data science, statistical physics, machine
    learning, theoretical and experimental biophysics, in different
    organizations of the Laboratory (T-6: Theoretical Biology and
    Biophysics Group; CCS-3: Information Sciences Group; T-5: Applied
    Mathematics and Plasma Physics).


For details, please visit jobs.lanl.gov and search for the unique IRC 
identifiers.

Potential candidates can make informal inquiries to Yen Ting Lin 
(yentingl at lanl.gov).

Los Alamos National Laboratory is an equal opportunity employer and 
supports a diverse and inclusive workforce. All employment practices are 
based on qualification and merit, without regard to race, color, 
national origin, ancestry, religion, age, sex, gender identity, sexual 
orientation or preference, marital status or spousal affiliation, 
physical or mental disability, medical conditions, pregnancy, status as 
a protected veteran, genetic information, or citizenship within the 
limits imposed by federal laws and regulations.  The Laboratory is also 
committed to making our workplace accessible to individuals with 
disabilities and will provide reasonable accommodations, upon request, 
for individuals to participate in the application and hiring process. To 
request such an accommodation, please send an email to 
applyhelp at lanl.gov or call 1-505-665-4444 option 1.

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