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AI systems and interpretable machine learning, System integration implementation, Test environment configuration, Validation and stress testing, Deployment and configuration in test environments
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skills with experience in cloud data warehouse systems such as Snowflake and data preparation tools like Tableau Prep Experience with predictive modeling, machine learning, AI applications, and advanced
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, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is
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execution and milestone completion. Job Requirements Strong background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software
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-omics liquid biopsy data for minimal residual disease (MRD) detection, quantification, and assessment. This project will involve applying and evaluating statistical and machine learning models for data
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learning video-AI models; b) assess representational alignment of bio-inspired deep learning models to the human brain. The bio-inspired models will be enriched with different temporal integration mechanisms
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root architecture and soil characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular
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and machine learning based modelling. Publish research data, prepare project progress reports. Assist in the preparation of grant proposals. Job Requirements: At least a Bachelor's degree from a
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these short-lived events are notoriously hard to reconstruct and to model, so our understanding of their behaviour during warmer climates is limited. To learn from past warmer climates and better understand
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composites for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization