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, wearable physiological sensing, and machine learning to uncover how factors like fatigue and cognitive workload impact technician performance. Join us to develop predictive models that predict human error
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and accelerate the development of more high-performing PNSEs. The ultimate goal of the project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained
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an advantage if you have Interest in the mechanical behavior of materials. Experience with machine learning and/or programming/coding. Experience with finite element modeling from civil, mechanical, or marine
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of the following areas: robotics, machine learning, robot perception, underwater systems, nonlinear control, system modelling, or autonomous manipulation Strong programming skills and a solid
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. Experience with programming, modelling, statistical analysis, or the use of data analytics, machine learning or artificial intelligence methods is desirable. Personal qualities Strong ability to follow through