Postdoc opportunity at Los Alamos National Laboratory

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    dblueeye
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    The Theoretical Biology and Biophysics Group (T-6) in the Theoretical Division at Los Alamos National Laboratory (LANL) is recruiting a highly motivated post-doctoral research associate. 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 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).

     

    Minimum Job Requirements

    A PhD in Physics, Data Science, Machine Learning, Bioinformatics, Applied Mathematics, Applied Statistics, Computer Science, or related fields completed within the last four years

    Hands-on experience in modern statistical inference, machine-learning, and/or bioinformatics

    Proficiency in probabilistic reasoning and uncertainty quantification

    Ability to conduct independent and collaborative research

    Scientific/numerical programming experience in Julia, C++, Python, or MATLAB

    Ability to organize and prioritize tasks under tight time constraints for effective achievements of project goals

    Excellent interpersonal, oral, and written communication skills

    Strong track record in data science, machine learning, or quantitative biology

    Education/Experience: A Ph.D. in computer science, physics, theoretical chemistry or biophysics. The candidate must have completed all Ph.D. requirements by commencement of the appointment and must be within five years of completion of the Ph.D. Candidates may also have previous experience including postdoctoral experience.

     

    Desired Qualifications

    Proficiency in Python, in particular, TensorFlow or PyTorch

    Proficiency in Julia

    Ability to adapt to new requirements for projects and be flexible to learn new computational tools

    Experience in applying data-driven methods on real biological datasets

    Experience in software engineering

     

    Note to Applicants

    The application package consists of a CV and a cover letter. In addition to applying online (please search for IRC88412 at http://jobs.lanl.gov), applicants may email their CV and cover letter to William S. Hlavacek (wish@lanl.gov) or Yen Ting Lin (yentingl@lanl.gov). Exceptional candidates may be considered for a Center for Non-Linear Studies Postdoc (for more information, see http://cnls.lanl.gov) and/or Director’s Fellowship. Outstanding candidates may be considered for the prestigious Marie Curie, Richard P. Feynman, J. Robert Oppenheimer, or Frederick Reines Fellowships.  For general information about the Postdoc Program, including salary guidelines, go to http://www.lanl.gov/careers/career-options/postdoctoral-research/postdoc-program/index.php.

     

    Where You Will Work

    LANL has an intellectually diverse environment and demands creative, innovative and pioneering solutions. LANL is a leader in high performance computing and has a history of leadership in this area, dating back to one of the first supercomputers ever built. The Theoretical Division was first led by Hans Bethe and was home to Richard Feynman for many years. As a national laboratory, high priority is placed in interdisciplinary studies. Facilities include one of the largest supercomputers in the world, four divisions (~300 people each) devoted to computation, and a significant computing allocation. We are located in the mountains of northern New Mexico, 40 minutes from Santa Fe, with close access to skiing, hiking, climbing and mountain biking.

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