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Operations Research or Decision Science Postdoctoral Research Associate

Company: Battelle Energy Alliance
Location: Idaho Falls
Posted on: May 3, 2021

Job Description:

Description



Job Information



Job Title: Postdoctoral Research Associate

Org: Advanced Data Analytics

Contact: Thomas.Steele@inl.gov

Work Location: Idaho Falls, ID (Town, Work Schedule - 9X80s)













Mission/Vision Statement






Empowering the Nation's Energy Future



Mission: Discover, demonstrate and secure innovative nuclear energy solutions, other clean energy options and critical infrastructure.



Vision: INL will change the world's energy future and secure our critical infrastructure.






Equal Employment Opportunity



Idaho National Laboratory (INL) is an Equal Employment Opportunity (EEO) employer. It is the policy of INL to provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.




Women and People of Color are strongly encouraged to apply.








Responsibilities



The Idaho National Laboratory (INL) is seeking a well-qualified Postdoctoral Associate in operations research, data science, applied math, computer science or comparable discipline for the Data and Software Sciences Department. This postdoctoral researcher will focus on formulating and applying mathematical modeling and optimization methods to develop and interpret information that assists management with decision making, policy formulation, and/or other managerial/R&D functions for complex, resilient energy systems and critical infrastructure. The candidate will play a key role in exciting research that 1) addresses critical and complex long-term challenges for overlapping sectors of critical infrastructure (e.g., power, transportation, water / wastewater, communications, supply chain considerations) and 2) evaluates a variety of energy challenges in biofuels, electrification of the grid, etc. in an effort to modernize the energy delivery system, enhance resilience of energy infrastructure, and identify best path to recover from disruptions to the energy system.

The position requires the following knowledge: develop complex optimization models using linear programming, integer programming, non-linear programming, bi-level optimization, stochastic programming, and dynamic programming to support decision-making. Implement and stay abreast of state-of-the-art exact algorithms/decomposition methods/heuristics methods used to solve large-scale mathematical models.

The successful candidate will have a strong background in data science as well, including knowledge of how to collect and clean large volumes of unstructured data for exploratory data analysis, feature engineering, machine learning (clustering, classification, regression models), validation, and visualization of knowledge to inform decision makers. Specifically, the successful candidate will have hands-on experience with databases and programming languages (relational; non-relational including graph-based such as SQL, NOSQL, OrientDB, Neo4j), object-oriented programming (C++, Python), mathematical and data science modeling packages (e.g., CPLEX, Gurobi, GAMS, MATLAB, Python for data science, R, Tableau, SAS)

The candidate is expected to be a strong asset to our interdisciplinary R&D team and work effectively both alone and as a team member. The candidate must be self-motivated but also take direction from other team members and peers.

The position entails collaboration with cross-functional research teams, writing scientific manuscripts for journal publication, presentation of research results to internal and external audiences, at national and international conferences and meetings, and, as appropriate, proposing new research concepts and work with team members to write and submit proposals for new opportunities. The candidate will also remain current with the literature in their technical domain.












Qualifications* PhD requirements must be completed by commencement of appointment and within the previous 5 years

* PhD in operations research, data science, applied math, computer science or comparable disciplines

* Demonstrated oral and published written communication skills

* Experience in developing complex optimization models

* Advanced knowledge of optimization algorithms for non-linear programming/mixed integer linear programming/ stochastic programming/bi-level optimization

* Ability to implement optimization model by integrating data base language (e.g. SQL), open source/ commercial solver, ( e.g. CPLEX ) and object oriented programming language ( C++, python)

* Good skills in object oriented programming language (C++, Python)

* Experience in data science workflow, including exploratory data analysis, feature engineering, clustering, classification, regression model building

* Familiarity with databases and languages (relational, non-relational)











Selective Service Requirements






To be eligible for employment at INL males born after December 31, 1959must have registered with the Selective Service System (SSS). This includes U.S. born and naturalized citizens, parolees, undocumented immigrants, legal permanent residents, asylum seekers, refugees, and all males with visas of any kind which expired more than 30 days ago. The few individuals who are exempt from this requirement are those on current non-immigrant visas. For more information see.













Employee Job Functions






Employee Job Functions are physical actions and/or working conditions associated with the position. These functions may also constitute essential functions for the job position which the employee must be able to fulfill, with or without accommodation. Information provided below is to help describe the job so that the applicant has a reasonable understanding of the job duties/expectations. An applicant's ability to perform and/or tolerate these actions and conditions will bediscussed and workplaceaccommodations maybe made on a case-by-case basis following an individualized assessment of the applicant and other considerations, including but not limited to any governing safety standards.



Standing - prolonged,Bending/stooping,Squatting,Fine motor control (hands),Visually demanding work,Audio alarms,Ability to smell,Stairs,Radiation work,Hazardous chemical/waste,Protective clothing,Typing/keyboard,> 8 Hrs/day







Please Apply Before: September 20, 2020 (Midnight)

















Environmental, Safety and Health Statement



Must be familiar with, and comply with all relevant health and safety requirements. Must be knowledgeable of emergency action policies and procedures, methods for reporting/resolving work practices or conditions to available cognizant professionals.




Other Information



When applying to positions please provide a resume and answer all questions on the following screens. Applicants, who fail to provide a resume or answer the questions, may be deemed ineligible for consideration.




INL Overview



INL is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research, science, and national defense. With more than 4,300 scientists, researchers and support staff, the laboratory works with national and international governments, universities and industry partners to discover new science and develop technologies that underpin the nation's nuclear and renewable energy, national security and environmental missions.






The Idaho Falls Area



Idaho Falls is conveniently situated near many national treasures such as Yellowstone National Park, Teton National Park, Jackson, WY, etc. For more information about the area, please visit www.visitidahofalls.com and .












Primary Location:US-ID-Idaho FallsJob:PostdocSchedule:Full-timeEmployee Status:RegularJob Posting:Feb 2, 2021, 7:08:56 PMUnposting Date:Ongoing

Keywords: Battelle Energy Alliance, Idaho Falls , Operations Research or Decision Science Postdoctoral Research Associate, Other , Idaho Falls, Idaho

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