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framework such as Tensorflow, Pytorch, MXNet and Programming Languages such as Python, Matlab, R and/or C/C++. Demonstrated project experience related to causal inference will be an advantage. Good written
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such as Python We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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, or a related field. Expertise in deep learning, multimodal LLMs, and Vision-Language-Action models. Strong programming skills in Python, with significant experience in PyTorch. Hands-on experience with
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gdsfactory. Knowledgeable in MATLAB and Python is necessary. Knowledgeable in Ansys Lumerical FDTD, MODE, INTERCONNECT, CML COMPILER, MULTIPHYSICS We regret that only shortlisted candidates will be notified
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++/Python. Excellent communication and collaboration skills. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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user friendly scripts in R, and Python for data visualization and analysis that can be used by other team members. ● Creative problem solver with critical thinking skills and the ability to manage
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user friendly scripts in R, and Python for data visualization and analysis that can be used by other team members. ● Creative problem solver with critical thinking skills and the ability to manage
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-reviewed publications in high-quality journals. • Proficiency in programming and modelling tools (e.g., R, Python, C/C++, Julia). • Excellent quantitative and analytical skills, with experience handling
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studies, QTL studies, colocalization, Mendelian Randomization) Proficient in R, Python, Linux/Unix Command over commonly used genetics (e.g., PLINK, GCTA, FUMA, variant predictor tools) and metagenomics