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. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
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for single-cell and spatial omics Deep learning and representation learning to model cellular states and interactions Explainable AI for biomarker discovery and patient stratification Cross-disease modeling
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learning to our students. We are interested in applicants with a PhD in a relevant discipline, alongside professional experience in an engineering or engineering-related environment. Experience
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Assistant Professor Positions in University Science Education Research: Learning Environments, Ex...
University Science Education Research, with a particular focus on learning environments, experience and design. All positions contribute to research on how learning environments and experience shape student
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reports to develop computational models that predict identification reliability. They will learn to design interpretable, legally robust AI systems, including attention-based deep learning models and
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. Contribute to Europe’s photonics ecosystem through involvement with PITC, JePPIX, and Chips for Europe initiatives Where to apply Website https://www.academictransfer.com/en/jobs/358372/phd-on-compact-models
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intelligence, machine learning, deep learning, computer vision, natural language processing, biocomputation, numeral networks, generative artificial intelligence, or mathematical modelling who can: Conduct high
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research groups focused on molecular biosensing for point-of-use applications. To learn more, visit MOBIUS website at https://mobius.org.au/ The primary objective of MOBIUS is to accelerate the growth
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: Experience with deep learning frameworks like PyTorch Experience in LLM development and/or evaluation Language requirement: Good oral and written communication skills in English English requirements
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to the supervision of PhD and/or Master’s students. Foster and sustain meaningful collaborations across local and national networks, including academic disciplines, professional sectors, relevant industries, and the