Post-doctoral Researcher – Statistical Learning and Modeling

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🕒 August 5

⛰️ Colorado – Remote

⛰️ Colorado – Remote

💵 $76.6k - $126.4k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👻 Ghost score 8%

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Advanced Energy Systems - Colorado School of Mines & NLR

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11 - 50 employees

Founded 2019

📚 Education

⚡ Energy

🔬 Science

Education • Energy • Science

Advanced Energy Systems - Colorado School of Mines & NLR is an interdisciplinary graduate engineering program created through a partnership between the Colorado School of Mines and the National Laboratory of the Rockies (NLR). The program educates and trains master’s and doctoral researchers to address the technical, economic, and environmental challenges of modern energy infrastructure, emphasizing secure, resilient, and adaptive systems. Students collaborate with faculty and NLR researchers, use shared state-of-the-art facilities, work with industry, government, and nonprofit partners, and prepare for careers solving large-scale energy-system problems.

📋 Description

• Develop statistical and machine learning techniques and associated software to characterize, model, and fuse multiple sources of information • Characterize disruptive events and their impacts on infrastructure such as power grids • Evaluate and communicate research results through written reports and presentations • Participate in group meetings and seminars • Assist in engineering and writing statistics and deep learning software • Conduct statistical and probabilistic data analysis • Design algorithms and develop publications • Draft and publish technical reports, conference papers, and journal publications • Attend and present research at technical conferences • Collaborate with multidisciplinary research teams, industry, academia, and other national laboratories

🎯 Requirements

• Recent PhD graduate within the last three years • Ph.D. in Statistics, Applied Mathematics, or Data Science • Must meet educational requirements before employment start date • Demonstrated experience developing statistical methods, including theoretical foundations, modeling, and computational aspects • Demonstrated experience developing methods for dimension reduction and uncertainty quantification • Demonstrated experience using deep learning software such as PyTorch • Demonstrated experience handling scientific datasets, including computer model simulations and observational data • Excellent verbal and written scientific communication skills • Demonstrated experience working with interdisciplinary teams • Demonstrated programming experience in Python and R • Experience with version control software • Demonstrated experience working on collaborative projects • Self-motivated and independent thinker • 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 be authorized to access the NLR facility under DOE rules • Must be able to obtain work authorization and DOE access approval • DOE contractor employees may be prohibited from participating in certain Foreign Government Talent Recruitment Programs

🏖️ Benefits

• 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 • Performance-, merit-, and achievement-based awards with a monetary component may be available • Relocation expense reimbursement may be available • Robust professional development opportunities • Competitive benefits package

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