Deep Learning Graduate Research Associate, Los Alamos National Laboratory

Website Los Alamos National Lab

We have an immediate opening for a creative and resourceful Deep Learning Graduate Research Associate with strong computational skills and experience in any of the following areas including seismic waveform inversion, imaging, earthquake detection, and characterization. We are seeking a highly motivated individual to join a multidisciplinary research team consisting of machine learning scientists, computational scientists, and domain experts to conduct cutting-edge machine learning research with application to various geophysical problems.

Minimum Job Requirements:

– Strong computational science and numerical optimization skills in any of the following areas including, seismic waveform inversion, imaging, and earthquake detection, and characterization
– Strong deep learning skills and practical experience in various neural network architectures (DNN, CNN, RNN/LSTM, GAN, or other auto-encoder)
– Practical experience with machine learning packages such as PyTorch, TensorFlow, Keras, etc.
– Code development and computational experience in using high-performance parallel computing resources.
– Solid publication record in high-impact journals, top-tier machine learning, and related conferences.
– Excellent communication, writing, and oral presentation skills, and

Desired Skills:

– Demonstrated ability to work creatively and independently and in a team environment.

Minimum Education:

– Completion of a Master’s degree in Geophysics, Applied Mathematics, Computer Science, Electrical Engineering, Computational Sciences, or a related field within the past 3 years.
– Cumulative GPA of at least 3.2 is required.

To apply, please search for IRC86144 under https://www.lanl.gov/careers/; or use the following direct link to the position:

https://lanl.jobs/los-alamos-nm/deep-learning-graduate-research-associate/0249C2BCCB5040E4B0943C7C0118DE6E/job/

Additional information about this position can be obtained by contacting Dr. Youzuo Lin (ylin@lanl.gov).

To apply for this job please visit lanl.jobs.