Postdoctoral Researcher – Numerical Optimization, Experimental Design

Advanced Energy Systems - Colorado School of Mines & NLR

. Pursue a cross-disciplinary research project in optimization and adaptive experimental design for cross-scale scientific applications .

Posted 11/9/2026full-timeGolden • Colorado • United StatesMid-LevelSenior💰 $76,600 - $126,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in optimization methodologies, including Bayesian optimization and active learning, while effectively collaborating within multidisciplinary teams. Proficient in developing experimental design strategies that maximize information and improve model predictions.

Highest-signal resume keywords

PhD In Relevant FieldBayesian OptimizationActive LearningExperimental Design StrategiesScientific Computing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Numerical OptimizationOptimal Experimental DesignSequential Decision-MakingInformation TheoryAdaptive SamplingSurrogate-Based OptimizationMulti-Fidelity SamplingMulti-Objective OptimizationAlgorithm DevelopmentMachine Learning

Soft Skills

Excellent Communication SkillsCollaboration

Tools & Technologies

PythonVersion Control

Certifications & Qualifications

Personal Identity Verification (PIV) Card

Industry Keywords

Cross-Scale Scientific ApplicationsHeterogeneous EvidenceDecision TheoryInformation GainValue Of Information

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Pursue a cross-disciplinary research project in optimization and adaptive experimental design for cross-scale scientific applications
Develop optimization and sampling methods leveraging predictions from models trained on cross-scale heterogeneous evidence and corresponding uncertainties
Determine which experiments to run, measurements to collect, and operating conditions to use to maximize information for improving model predictions
Develop original methodologies in numerical optimization, optimal experimental design, active learning, Bayesian optimization, sequential decision-making, information theory, adaptive sampling, surrogate-based optimization, and statistical design of experiments
Address noisy, messy, missing, or sparse data and models with uncertainty
Collaborate with multidisciplinary research teams and industry, academia, and other national laboratories

Requirements

What you’ll need

Recent PhD graduate within the last three years
Must meet educational requirements prior to employment start date
Experience developing optimal experimental design strategies
Strong background in selecting experiments to maximize information, identify parameters, distinguish hypotheses, or improve model predictions
Experience developing active learning and sequential design methods
Experience with Bayesian optimization, including acquisition functions, surrogate models, and sequential optimization
Experience with multi-fidelity, multi-modal, multi-source sampling
Understanding of information theory and decision theory, including information gain and value of information
Understanding of constrained and cost-aware sampling methods
Experience modeling constrained and multi-objective optimization problems
Experience in scientific computing and optimization
Ability to develop and implement efficient algorithms for sequential decision-making
Excellent communication skills
Experience working in multidisciplinary teams and collaborative software development
Experience with machine learning and AI
Demonstrated experience with Python and version control
Must be able to obtain and maintain a federal Personal Identity Verification (PIV) card
Must pass a favorable background investigation
Must pass a pre-employment drug test
Must submit a cover letter and resume with the application

Benefits

Comp & perks

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
Paid holidays
Eligibility for performance-, merit-, and achievement-based awards with a monetary component
Relocation expense reimbursement may be available for some positions
Robust professional development opportunities