Join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. Work on cutting-edge research in new and emerging fields.

Requirements

PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference.
Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
Proven ability to undertake original research and communicate findings in peer-reviewed publications.
Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Benefits

Join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. Work on cutting-edge research in new and emerging fields.

PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference.
Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
Proven ability to undertake original research and communicate findings in peer-reviewed publications.
Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.