Employment Type: Full Time Salaried Employee
Location: Houston, Texas, United States
We are looking for the right people - people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world's largest providers of products and services to the global energy industry.
Senior Tech Prof-Technologist
We are seeking a geophysicist with an interest in machine learning to join our team in Houston to develop innovative approaches in geophysical processing, inversion, or interpretation for the energy sector. Successful candidates will work alongside a team of experienced geophysicists, geoscientists, and software developers. You will be responsible for the design and implementation of solutions that will improve geophysical workflows for our customers.
We are looking for a candidate with strengths in one or more of the following subject areas:
- Applied mathematics
- Geophysical processing, inversion, or interpretation
- Geoscientific data analysis
- Machine Learning
- Deep Learning
- Under general supervision, you will assist in the design and implementation of new data driven solutions for Landmarks Computational Science and Engineering for Energy Organization
- Skills are typically acquired through the completion of a PhD in a numerical science or computing subject
- Ideal candidates will have technical experience of applying data science techniques to solve technical problems
- Experience in geophysical processing, inversion, or interpretation
- Technical experience with scientific programming languages (e.g., Python, C++, java, FORTRAN)
- Experience in using common data science libraries (e.g., pandas, numpy, scipy, scikit-learn, keras, tensorflow, pytorch, etc.)
- A strong background in applied mathematics, data analysis, statistics, linear algebra, or machine learning
- Ability to effectively communicate your work and ideas with specialists and non-specialists.
- Strong organization and project management skills
- Experience with geoscience data types (LAS, SEG-Y, etc.) and databases (OpenWorks, Recall, etc.)
- Experience of working in remote teams across multiple time zones
- Experience with physics-informed neural networks, Fourier-neural operators, and hybrid deep-learning methods
Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs. Depending on education, experience, and skill level, a variety of job opportunities might be available
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
3000 N Sam Houston Pkwy E , Houston , Texas , 77032 , United States
Requisition Number: 123616
Experience Level: Experienced Hire
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Additional Locations for this position:
Founded in 1919, Halliburton is one of the world’s leading providers of products and services to the upstream energy industry.
Halliburton is proud to be a services company, and our customers and investors appreciate our business model. Our strong competitive position not only comes from our geographic footprint and wide range of products and services, but also, more importantly, from the quality of our work and the dedication of our employees.
With approximately 55,000 employees, representing 140 nationalities in more than 80 countries, Halliburton touches much of the oil and gas that fuel our society.
Halliburton comprises 14 product service lines (PSLs). The PSLs operate in two divisions: Drilling and Evaluation, and Completion and Production.
Our Consulting and Project Management PSL works across both divisions and is the spearhead of our integrated-services strategy. Its financial results are included in the Drilling and Evaluation Division. PSLs are primarily responsible and accountable for strategy, technology development, process development, people development and capital allocation.
Integrity: Ethics and integrity are the foundation of our brand and the guiding principles for all we do.
Safety: Priority number one. We are focused on our own personal safety, as well as on the safety of others.
Collaboration: We work together with customers, and understand that everyone has a role in providing the best solution.
Competition: We compete to win, knowing that competition makes everyone stronger.
Creativity: We are resourceful. We are innovative, and strive to apply the right technology and solution every time.
Reliability: We deliver what we promise. We believe the quality of our service defines who we are.
Respect: We are honest with ourselves and with each other. We value our diverse skills and talents, and know we are stronger together as one family.
These values are our corporate DNA, the foundation for how we relate to each other and to every individual and entity with whom we interact. These are the principles that every Halliburton employee is expected to use, live by, and demonstrate on a daily basis.
Own Your Career
Our people are essential to our ability to innovate, achieve, grow, and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. We invest in our employees through leadership and competency development, competitive compensation plans, health benefits, work-life programs, and reward and incentive plans.
Opportunities for career development – and the tools you need to take advantage of them – are abundant. Combine those opportunities with your drive and capabilities, and your career path can go in nearly any direction you choose.