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Babinski, PhD. This position will report to Research Professor Leslie Babinski. CIDR is a school-based research and professional learning initiative designed to strengthen adolescent wellbeing and literacy
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Triple Negative Breast Cancer Using Machine Learning”. We seek to appoint a creative and motivated individual to use machine learning (ML) to identify why some patients with triple negative breast cancer
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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on the research strengths in bioengineering, data analytics, artificial intelligence, and machine learning. More information on our research strengths can be found at https://www.uta.edu/academics/schools-colleges
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preferred Excellent knowledge of microeconometric methods for causal inference; knowledge of machine learning methods is preferred Experience in university teaching Strong communication and teamwork skills
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possibility of extension) Start date: August 2026 at latest The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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and Geophysics. Candidates should have a PhD in geology, geophysics or related field by the time of this appointment, be within 5 years of their PhD and have not held a permanent or tenured faculty
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate 51 Faculty of Physics Startdate: 01.04.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr
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% of the fellowship time to personal research. This is a one-year fellowship appointment, with the possibility of renewal for two additional years. Applicants must have fulfilled all the requirements for the PhD by