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Field
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site-specific and realistic radio propagation data through GPU-accelerated ray tracing to train AI/ML algorithms. Exploring the use of generative models for wireless channel modeling, e.g., to produce
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: Neural networks and machine learning. Algorithm. Professional Experience: In the use of Python (PyTorch, TensorFlow) and C for the development and optimization of deep learning algorithms. Experience in
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, and Lifelines. Groups of patients with different prognoses will be identified through unsupervised clustering using algorithms such as K-means and NMF. To evaluate the tumor microenvironment, tools
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these data structures and their associated algorithms to enable pattern-matching and other operations required, for instance, to infer microbial transcriptional regulatory networks through comparative genomics
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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background in computer science or biomedical engineering, with a strong focus on programming using deep learning libraries and machine learning algorithms. Demonstrated experience in medical image processing
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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of electronic systems. Simulation and design of power electronic converters. Programming of control algorithms for electronic converters. Hardware design of electronic control and power circuits
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Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient. JOB LOCATION AND SCHEDULE: CITIC. Monday to Friday, from 10:00 a.m. to 2:00
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group