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programmable connectivity systems. The successful candidate will conduct research at the intersection of AI and networking, contributing to advanced architectures and intelligent, sustainable connectivity
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of chromosomes and specific DNA sequences within the nucleus influences gene expression by visualizing nuclear architecture combining molecular biology, biochemistry, and super-resolution imaging methods
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
(perfusion imaging) and response to radiotherapy assessment. These models will explore recent diffusion and auto-regressive generative architectures. They will leverage Mixture of Experts, Chain of Thought and
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device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. Exploring hardware-level security mechanisms based
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develop and integrate cutting-edge experimental and computational platforms: Large-cohort single-cell genomics (e.g., TenK10K) generating millions of profiles to map regulatory architecture across diverse
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. To achieve this, we develop and integrate cutting-edge experimental and computational platforms: Large-cohort single-cell genomics (e.g., TenK10K) generating millions of profiles to map regulatory architecture
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of neural network architectures (as a plus: PINNs, neural operators, transformers/LLM) and NN training. Strong Python programming skills (as a plus: C++ or Julia) and knowledge of scientific computing
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networking (SDN), network function virtualization (NFV), and container-based network architectures. The ideal candidate will possess not only a solid theoretical understanding of these technologies but also a
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neurodifferentiation and cancer models. Candidates with strong interest in gene regulation, chromatin architecture, epigenetic mechanisms, and non-coding RNA biology are encouraged to apply. Experience in performing and
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Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures) to large-scale biomedical