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to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The Team is looking to appoint one Postdoctoral Research Associate on Machine-Learning Assisted
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Facilities: On site Car Parking On site dining facilities On site TFI Bike Sharing Station Eligibility criteria MTU is seeking persons with a relevant PhD qualification and suitable experience to fill the
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. DVXplorer), and tactile/force sensors. Strong background in computer vision and deep learning, with practical implementation experience. Proficiency in programming with C++ and Python, including use of ROS
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opportunity for someone who thrives in an interesting and challenging work environment. Core responsibilities include: Research in the intersection of discrete optimization and machine learning, including
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no.: 4644 Explore and teach at the University of Vienna, where over 7,500 academic minds have found a unique blend of freedom and support. Join us if you're driven by a passion for top-notch international
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., knowledge representation and reasoning) and bottom-up (e.g., machine learning) methods to study the representation of geographic categories and processes. While we welcome applicants from a broad range of
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engineering capability in machine learning while demonstrating the potential and impact of this knowledge for industries in Australia. To be successful you will need: A completed PhD or a submitted PhD thesis
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submitted his/her doctoral thesis for assessment prior to the application deadline. It is a condition of employment that the PhD has been awarded. Applicant should have a genuine interest in AI the learning
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access
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-based cameras (e.g. DVXplorer), and tactile/force sensors. 3. Strong background in computer vision and deep learning, with practical implementation experience. 4. Proficiency in programming with