Major Duties and Responsibilities:
Senior Scientists/R&D Staff at ORNL bring together a group of peers with the primary goal of pursuing global scientific leadership in their field and developing strategies to build a world class research capability. These position’s report to a Group Leader and work closely with R&D Section Heads to implement the group’s scientific vision; establish capabilities that enable programs to excel at the forefront of science and technology; perform R&D to advance the field of knowledge and/or technology in one’s respective specialty; develop group members to enable their career advancement; sets, implements, and models standards for performance of work consistent with Environment, Safety, Security, Health, and Quality (ESH&Q) requirements and business rules; and ensures a diverse and inclusive work environment where every employee feels safe, heard, and appreciated—a workplace that sets an example for the broader community.
This position will specifically will:
- Work in a highly collaborative environment with data scientists, machine learning scientists, remote sensing scientists, computer scientists, engineers, physicists, and geographers to deliver tools, methods, and solutions from prototyping to production level.
- Establish and grow a research portfolio around modeling and simulation of the built environment.
- Initiate, lead, and perform independent and team-based innovative R&D that delivers impactful S&T artifacts for sponsors, including but not limited to proposals, technical presentations and technology demonstrations, and inventions/patents/copyrights, etc.
- Advance the reputation of the Group, Section, Division, and Lab through engaging and collaborating in the research community and serving as a leader in your domain as a representative of ORNL.
- Publish in top tier conferences and journals.
- Identify opportunities to expand existing and grow new research areas with sponsor organizations.
- Assist the R&D Group Lead and Section Head with staff development and mentoring, while providing direct and impactful guidance to staff on regular basis.
- Lead by example through exercising scientific integrity in proposing, performing, and communicating research.
- Lead by example to ensure all work is carried out safely, securely, and in compliance with ORNL policies, standards, and procedures.
- Exemplify a commitment to excellence in research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL.
- Ph.D. with a minimum of 8 years' relevant experience or M.S. with a minimum of 12 years’ relevant experience.
- Degrees in relevant fields, such as operations research, engineering sciences, computer science, or GIScience.
- Demonstrated track record of research and science leadership.
- Background in building and implementing models and tools that describe and predict interactions in the physical world.
- Ability to build modeling and simulation approaches to assess infrastructure and supply chain resilience.
- Familiarity with approaches and tools for uncertainty quantification.
- Excellent interpersonal skills with a demonstrated leadership ability and a strong commitment to a teaming environment.
- Strong written and oral communication skills.
- Demonstrated project management experience.
- Expertise in writing scientific tools using R, Octave, and MATLAB.
- Familiarity with modern software languages like Python and C/C++.
- Experience with common approaches to optimization, including linear, non-linear, and stochastic programming.
- Experience with complex systems simulation.
- Experience in designing and implementing optimization models for discrete and combinatorially complex problems (e.g., routing, facility location, supply chain modeling).
- Experience with agent-based and physics-based modeling techniques and software.
- Experience working with large-scale static and dynamic network-based datasets.
- Familiarity with data science and machine learning techniques.
- Experience in collaborating with DOE National Laboratories, academic institutions, other research organizations, and the private sector.
- Familiarity with research and development programs and priorities of Federal agencies.