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Research & Development Engineer 2 (4757C) – NanoLab

About Berkeley

At the University of California, Berkeley, we are dedicated to fostering a community where everyone feels welcome and can thrive. Our culture of openness, freedom and belonging make it a special place for students, faculty and staff.

As a world-leading institution, Berkeley is known for its academic and research excellence, public mission, diverse student body, and commitment to equity and social justice. Since our founding in 1868, we have driven innovation, creating global intellectual, economic and social value.

We are looking for applicants who reflect California’s diversity and want to be part of an inclusive, equity-focused community that views education as a matter of social justice. Please consider whether your values align with our Guiding Values and Principles, Principles of Community, and Strategic Plan.

At UC Berkeley, we believe that learning is a fundamental part of working, and

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Are you excited about designing hardware that mimics biological intelligence with the aim to explore and understand how the brain works? Are you interested in developing hardware-based artificial intelligence (AI) with the goal of solving important societal challenges? Are you a passionate, self-motivated and creative researcher who is driven by solving important questions in neuroscience? If so, then the Semiconductors and Microelectronic systems (SAM) group at TU Berlin has an exciting PhD opening for you at the interface between nanoelectronic devices, computational materials science, neuroscience and AI.

We are seeking a candidate for a PhD position described as follows:

– Here, you will explore novel materials (including, magnetic, ferroelectric, 2D and correlated materials) and leverage their complex physics to design and simulate advanced nanoelectronic devices.

– These devices will replicate the finer workings of brain cells (neurons) and their connections (synapses) in the

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Postdoc/PhD/MASc/MEng Graduate Research Opportunities at 

Artificial Intelligence for Aerospace Systems (AIAS) Laboratory 

Department of Aerospace Engineering

Toronto Metropolitan University, Toronto, Canada

1)  Artificial Intelligence and Machine Learning-Powered Smart Aerospace Systems

The thesis/project will focus on designing novel artificial intelligence and machine learning-based algorithms to develop smart aerospace systems. Several investigations have been conducted at the AIAS laboratory in cooperation with aerospace companies and government agencies (including NASA, Canadian Space Agency, and MHICA) on the fault diagnosis, prognosis and recovery of aerospace systems. The results on aircraft/spacecraft control systems and aircraft engines are very promising for practical applications. The proposed research aims to further enhance the performance of these algorithms using artificial intelligence, machine learning and digital twins based methodologies for real-time fault diagnosis, prognosis and recovery applications.

2)  Cutting-Edge Internet-of-Things (IoT) Devices for Smart Aerospace Systems 

In recent years, significant advancements have been made in

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