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publishing high-quality research papers in top-tier conferences and journals. Proficiency in advanced programming and computational modeling tools (e.g., Python, distributed systems). Good written and oral
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial
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quantum many-body theory with a focus on quantum impurity models (particularly Kondo model). Strong computational skills (with Python or Julia or C++ or Matlab or equivalent) and using numerical techniques
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discipline from a strong institution. Skills: - Proficient in programming languages such as Python, with experience in using AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiar with high
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the context of technology sectors. He/she should have good programming/coding skills such as SQL, Python and/or Java and be competent with statistical packages like STATA or R (STATA preferred). Skill and
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programming language would be valued (e.g. Python, Matlab…) Self-driven, highly motivated, with interest to work with other researchers and scientists (as a team player) to produce high-quality research. We
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well as with a team. He/she is preferred to have experiences in: Microfluidic design and fabrication MatLAB and/or Python proficiency for data processing PCB designing and/or microprocessor programming (ARM
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and skill in programming with MATLAB or Python. Research experience in MEG, in vivo electrophysiology, in vivo two-photon/miniscope imaging, slice electrophysiology, and mouse brain surgery is desired
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learning methods to biological or clinical datasets. Proficiency in Python and R, with strong experience in Linux/HPC environments and workflow automation. Track record of publications in high-impact
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physics, with experience in thin-film deposition, device fabrication, and electrical transport measurements Familiarity with the theory of magnetism Proficiency in MATLAB/Python and LabVIEW for data