Postdoctoral Researcher – Computational Statistics

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Argonne National Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization methods that aim to transform scientific discovery and leverage high-performance computing.

Specifically, this will include research in:

1. Developing large-scale agent-based and other complex systems models;

2. Statistical methods, analysis, and inference for large-scale computational simulator applications;

3. Uncertainty representation, quantification and propagation; and

4. Scalable data science methods and software for the analysis and calibration using very large data sets resulting from dynamical simulations on high-performance computing resources.

Application areas include:

1. Epidemiology,

2. Energy infrastructure, and

3. Urban systems.

The postdoctoral appointee will contribute to at all stages of the implementation of the resulting methods from prototyping in high-level languages to the development in high-performance computing environments. They will work with a team of researchers  in the Decision and Infrastructure Sciences Division at Argonne and be part of interdisciplinary collaborations with other Argonne divisions, national laboratories, universities and industry partners.

Position Requirements

Knowledge in the following four areas:

1.  Modern methods for developing large-scale agent-based models, particularly for epidemiological applications;

2.  Data science and large-scale data analysis in high performance computing environments;

3.  Optimization, uncertainty quantification, and statistical analysis and modeling techniques such as Gaussian process modeling, data assimilation, and Bayesian analysis; and

4. Open-source scientific software development.

• Expertise in computational statistics and uncertainty quantification (Bayesian analysis, data assimilation, Gaussian process modeling), and their application to complex systems modeling.

• Experience in developing and applying statistical algorithms and software for large-scale scientific applications.

• Expertise in programming in a high-level language such as R or Python.

• Experience and skills in interdisciplinary research involving mathematicians, computational scientists, and discipline scientists.

• Should be able to interact effectively with members of a multidisciplinary team.

• Collaborative skills, including the ability to work well with scientists at other laboratories and universities.

• Should be able to develop, high-quality scientific reports.

• Independent judgment and the ability to abstract from specific problems to general solutions.

• Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

• To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required to comply with federal regulations and contract”

This level of knowledge is typically achieved through a formal education in a related field at the PhD level with zero to five years of employment experience.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

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