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Field
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Learning Video Understanding Multimodal AI Excellent programming skills in Python. Hands-on experience with: PyTorch Hugging Face Transformers OpenCV Experience working with deep learning models for image
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. Develop reproducible, version-controlled pipelines and notebooks in R and/or Python for high-performance computing environments. Coordinate data generation with clinical and experimental partners, including
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/optimization/programming software (e.g., HOMER, GAMS, and Python). Evidence of previous scientific writing or academic publications (e.g., peer-reviewed journals), industrial collaboration, knowledge transfer
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processing, and sensor integration. Strong background in signal processing, computer vision, or machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record
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of a PhD · Expert knowledge of statistical modelling, statistical inference and use of relevant software (e.g. R/Python) both for data processing, visualisation and programming. · Excellent communication
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confident in handling the relevant data and be competent in programming on either MATLAB or Python. You will also be enthusiastic about building and troubleshooting your experimental rig. You will have the
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: Lead computational analysis and integration of single-cell RNA-seq and spatial transcriptomics datasets on endometrium. Develop reproducible, version-controlled pipelines and notebooks in R and/or Python
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. • Proficiency in software development in R/Python. • Experience with high-dimensional mixed data types or integrative methodologies is desirable. Application Instructions Please submit the following materials
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, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow
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datasets (e.g., GWAS, RNA-seq) Proficiency in programming languages such as R or Python and experience with bioinformatics tools Strong planning and organising skills Excellent written and verbal