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Position Description and Responsibilities

We seek a talented Physicist/Mathematician with a PhD in Physics, Chemistry, or related science and engineering. Proven experience with NMR (Nuclear Magnetic Resonance) physics, as demonstrated by PhD or MSc Thesis and/or published work in the field is required. The ideal candidate for this position is an expert in NMR theory and measurements and can lead cutting edge research in the field. Excellent problem-solving ability and good oral and written communication skills in both English and Portuguese are required.

You will join a multidisciplinary and diverse team of scientists and engineers committed to delivering high-end computational technologies and tools for the O&G and broader Energy industry.

 

Your responsibilities will include, but will not be limited to:

Working in a multidisciplinary team of scientists developing simulation capabilities to predict the responses of various formation evaluation sensors including NMR sensors. Acquiring and analyzing laboratory NMR relaxometry data and designing experiments suitable to validate the NMR responses predicted by pore scale simulations. Developing NMR pore scale simulations in 3D rock image-based pore systems to simulate the NMR measurement responses.

 

What you must have:

Strong physics background including, but not limited to: Brownian Motion Dynamics, Hamiltonian theory, Liouville-space Spin Dynamics and/or methods for simulating nuclear spin relaxation in 3D models. Experience analyzing experimental NMR measurements. Experience with programming/scripting languages such as Python, C++, and/or Matlab.

 

What is nice to have:

Experience with NMR applications in well logging tools. Knowledge of scientific computing (e.g., linear and nonlinear solvers, numerical methods, etc.) Familiarity with computational mathematics (e.g., linear algebra, calculus, matrix decompositions, etc.) Knowledge of Rock Physics and Formation Evaluation (e.g., porosity-permeability, well logging methods, fluid distribution, etc.) Knowledge of fluid-flow physics (e.g., Navier-Stokes Equations, Multiphase Flow, etc.) Familiarity with open-source scientific computing libraries (e.g., HYPRE, BOOST++, PETSC, DUNE, LAPACK, etc.)

 

Compensation Information
Compensation is competitive and commensurate with experience.

 

 

Location

Opportunities may exist in multiple locations.

 

Job Details

Additional Locations for this position:

Requisition Number: 192201 
Experience Level:
Job Family: Information Technology
PSL: [[division_obj]] 
Full Time / Part Time: Full Time

 

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.