Overview
Georgia Tech prides itself on its technological resources, collaborations, high-quality student body, and its commitment to building an outstanding and diverse community of learning, discovery, and creation. We strongly encourage applicants whose values align with our institutional values, as outlined in our Strategic Plan. These values include academic excellence, diversity of thought and experience, inquiry and innovation, collaboration and community, and ethical behavior and stewardship. Georgia Tech has policies to promote a healthy work-life balance and is aware that attracting faculty may require meeting the needs of two careers.
About Georgia Tech
Georgia Tech is a top-ranked public research university situated in the heart of Atlanta, a diverse and vibrant city with numerous economic and cultural strengths. The Institute serves more than 45,000 students through top-ranked undergraduate, graduate, and executive programs in engineering, computing, science, business, design, and liberal arts. Georgia Techs faculty attracted more than $1.4 billion in research awards this past year in fields ranging from biomedical technology to artificial intelligence, energy, sustainability, semiconductors, neuroscience, and national security. Georgia Tech ranks among the nations top 20 universities for research and development spending and No. 1 among institutions without a medical school.
Georgia Techs Mission and Values
Georgia Techs mission is to develop leaders who advance technology and improve the human condition. The Institute has nine key values that are foundational to everything we do:
Over the next decade, Georgia Tech will become an example of inclusive innovation, a leading technological research university of unmatched scale, relentlessly committed to serving the public good; breaking new ground in addressing the biggest local, national, and global challenges and opportunities of our time; making technology broadly accessible; and developing exceptional, principled leaders from all backgrounds ready to produce novel ideas and create solutions with real human impact.
Atlanta, GA
The School of Earth and Atmospheric Sciences (EAS) is highly interdisciplinary and covers broadly all fields of Earth and space science. EAS hosts a range of undergraduate degrees, including B.S. programs in Atmospheric and Oceanic Sciences (AOS), Solid Earth and Planetary Sciences (SEP), and Environmental Science (ENVS), and hosts a distinct interdisciplinary Ph.D. program in Ocean Science and Engineering in collaboration with the School of Biological Sciences and Environmental Engineering. For more information about our School and academic programs, visit eas.gatech.edu.
Postdoctoral Fellow position in Seismic Laboratory for Imaging and Modeling (SLIM) at the School of Earth & Atmospheric Sciences at the Georgia Institute of Technology. The postdoctoral fellow will be part of a cross-disciplinary research team in (Computational Science & Engineering, and Electrical & Computer Engineering, (led by Felix J. Herrmann) addressing challenges of seismic monitoring of Geological Carbon Storage (GCS), wave-based imaging and [inverse] problems, and machine learning.
The successful appointee will be expected to undertake the following:
A PhD (or close to completion) in Earth Sciences, or possibly in a related field with a focus on areas such as numerical simulations, numerical linear algebra, statistical machine learning, and Bayesian Inference.
A PhD (or close to completion) in Earth Sciences, or possibly in a related field with a focus on areas such as numerical simulations, numerical linear algebra, statistical machine learning, and Bayesian Inference; a strong knowledge and excellent skills in at least two of the following areas: wave-based inversion (PDE-constrained optimization and adjoint-state methods); machine learning and uncertainty quantification (conditional normalizing flows, variational Bayesian inference); learned surrogates (Fourier neural operators, physics informed neural nets); and data assimilation (Kalman filters, sequential Bayesian inference). The candidate is also expected to be well versed in computational methods and programming (Python or Julia are essential) with experience in (scientific) machine learning and/or high-performance computing.
For additional information about this appointment, please contact: Felix Herrmann felix.herrmann@gatech.edu
The candidate of choice will be required to pass a pre-employment background screening. http://policylibrary.gatech.edu/employment/pre-employment-screening
The Georgia Institute of Technology (Georgia Tech) is an Equal Employment Opportunity Employer. The University is committed to maintaining a fair and respectful environment for all. To that end, and in accordance with federal and state law, Board of Regents policy, and University policy, Georgia Tech provides equal opportunity to all faculty, staff, students, and all other members of the Georgia Tech community, including applicants for admission and/or employment, contractors, volunteers, and participants in institutional programs, activities, or services. Georgia Tech complies with all applicable laws and regulations governing equal opportunity in the workplace and in educational activities.
Georgia Tech prohibits discrimination, including discriminatory harassment, on the basis of race, ethnicity, ancestry, color, religion, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin, age, disability, genetics, or veteran status in its programs, activities, employment, and admissions. This prohibition applies to faculty, staff, students, and all other members of the Georgia Tech community, including affiliates, invitees, and guests. Further, Georgia Tech prohibits citizenship status, immigration status, and national origin discrimination in hiring, firing, and recruitment, except where such restrictions are required in order to comply with law, regulation, executive order, or Attorney General directive, or where they are required by Federal, State, or local government contract.
All members of the USG community must adhere to the USG Statement of Core Values, which consists of Integrity, Excellence, Accountability, and Respect. These values shape and fundamentally support our Universitys work. Additionally, all faculty, staff, and administrators must also be aware of and comply with the Board of Regents and Georgia Institute of Technology's policies on Freedom of Expression and Academic Freedom. More information on these policies can be found here: Board of Regents Policy Manual | University System of Georgia (usg.edu).
We understand that being diverse makes us better which is why we support a culture of respect and equal opportunity, and value diversity at the heart of what we do. We wish to increase the diversity of our workplace to underpin a dynamic and creative environment, and strongly encourage applications from women, underrepresented minorities, individuals with disabilities, and veteran. We welcome and will consider flexible working patterns. Candidates with the skills and knowledge to productively engage with diverse communities are encouraged to apply.
The successful applicant will be given the support and mentoring required to develop their academic career in this key position at the forefront of world leading research. Please note that this job description is not exhaustive, and the role holder may be required to undertake other relevant duties relevant to the appointment. Activities may be subject to amendment over time as the role develops and/or priorities and requirements evolve. A flexible working schedule may be required to meet all key duties and responsibilities. We will measure applicants based on the essential criteria, not by the key duties.
While GCS is a promising technology to inject large amounts of supercritical CO2 into porous and permeable rock formations for long-term storage, there may be certain risks associated with this technology that call for reassurance of the public, regulators, and other stakeholders of its safety. Even for well-designed CO2 injection projects with accurately established baselines, there always remains a risk that the CO2 plume leaves the storage complex via e.g. focused fluid flows, porosity collapse, or changes in fracture networks. At the Seismic Laboratory for Imaging and Modeling (located within Coda at Tech Square), and as part of the industry partners program ML4Seismic, we are addressing these risks by embracing recent developments in simulation-based Bayesian inference-i.e., the task of deriving statistical information from a system based on in silico simulations-that allows us to develop low-cost, scalable, high-fidelity and uncertainty-aware seismic monitoring solutions for GCS. The research will be conducted at SLIM in collaboration with Edmond Chow and Ghassan AlRegib, co-director of ML4Seismic.