Postdoctoral Researcher in Numerical Optimization and Experimental Design

Posting Title
Postdoctoral Researcher in Numerical Optimization and Experimental Design

Location
CO - Golden

Position Type
Postdoc (Fixed Term)

Hours Per Week
40

Job Description

The Artificial Learning and Intelligent Systemsgroup in NLR's Computational Science Center has an immediate opening for a Postdoctoral Researcher to pursue a cross-disciplinary research project in optimization and adaptive experimental design for cross-scale scientific applications (lab-scale to pilot-scale) relevant to the DOE Office of Critical Minerals and Energy Innovation.

The successful applicant will develop optimization and sampling methods that leverage predictions from models that were trained on cross-scale heterogeneous evidence and their corresponding uncertainties. The sampling strategies must determine which experiments to run, which measurements to collect, or operating conditions to use in order to acquire the most information for improving model predictions at the target experimental scale. The successful applicant will develop original methodologies and have expertise in numerical optimization, optimal experimental design, active learning and Bayesian optimization, sequential decision-making and information theory, adaptive sampling and surrogate-based optimization, and statistical design of experiments. The ability to address challenges arising from applications with noisy, messy, missing or sparse data, and dealing with models that have uncertainty is a must.

Basic Qualifications
Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Demonstrated experience in developing optimal experimental design strategies with strong background in selecting experiments to maximize information, identify parameters, distinguish hypotheses, or improve model predictions.
• Demonstrated experience in developing active learning and sequential design methods for iteratively selecting new data points based on what has already been learned.
• Demonstrated experience in Bayesian optimization, including development of acquisition functions, surrogate models, and sequential optimization, ideally beyond standard black-box optimization.
• Demonstrated experience with multi-fidelity, multi-modal, multi-source sampling including making optimal decisions on where to sample, what conditions to test, which scale (lab to pilot) or level of fidelity to conduct an experiment.
• Understanding of information theory and decision theory with deep understanding of information gain, value of information, and the relationship between uncertainty reduction and practical decisions.
• Understanding of constrained and cost-aware sampling methods including accounting for experiment cost, time, feasibility, safety, and operational constraints when selecting experiments as well as experience modeling constrained and multi-objective optimization problems.
• Demonstrated experience in scientific computing and optimization including the ability to develop and implement efficient algorithms for sequential decision-making.
• Excellent communication skills
• Experience working in multi-disciplinary teams and collaborative software development
• Experience with machine learning and AI.
• Demonstrated experience with python and version control

Preferred Qualifications
• Self-motivated, creative, and independent thinker
• Open-minded and eager to learn about new application challenges

Job Application Submission Window

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400

NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.

Benefits Summary
Benefits include medical, dental, and vision insurance; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.

* Based on eligibility rules

Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.

Submission Guidelines

Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.