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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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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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, environmental sciences, geoinformatics, or a related discipline. Proficiency in advanced learning techniques and statistical modeling. Strong programming skills in languages like Python or R. Professional
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blow moulding. You will also have: Experience applying AI or coding tools (e.g. Python or MATLAB) to analyse scientific data A track record of conducting and interpreting experimental work The ability
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training deep learning models on biological, chemical or related datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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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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also being a mentor to other members of the community. KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED: Cancer biology background Experience in R and/or Python is preferred Experience with Linux-based shell
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), including during a postdoctoral fellowship. Experience with high-performance computing centers as well as with modern statistical software (R, etc.) and programming languages (Python, etc.). The candidate is
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molecular dynamics and machine learning. The candidate should have proficiency in scientific programming with Python or C++ and familiarity with machine learning libraries like Torch or TensorFlow
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such as Python We regret that only shortlisted candidates will be notified. Hiring Institution: NTU