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. Position You will work actively on the preparation and defence of a PhD thesis focusing on machine learning-based forecasting of renewable energy production, with a particular focus on wind energy. The
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mutations, etc.), analysis and integration of mass-spectrometry proteomics datasets, and artificial intelligence/machine learning (AI/ML) and systems-biology-focused efforts (i.e. large genomics and
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, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation
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) for science with Dr. Aleksandra Ciprijanovic (alexciprijanovic.com) and her research group! The successful candidate will join a multidisciplinary team working at the intersection of deep learning, cosmology
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Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g
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strong foundation in either data science, electronics, or systems engineering—with a deep curiosity to learn the others. Professional qualifications: Educational background: You hold an MSc in
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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solutions that enhance ecological monitoring, improve resilience planning, and promote sustainable resource management. Development of a Detection Transformer through Attentive Deep Learning and Explainable
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, or geometric deep learning. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage
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learn to apply these processes judiciously while maintaining a focus on originality and professional integrity. Candidates should have a relevant Master’s and/or PhD in Digital Arts, Computational Media