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. This position, funded by ALRI, offers an initial one-year appointment, with renewal contingent upon availability of funding. Cnducts cutting-edge research in artificial intelligence, machine learning
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background/interest in time-series analysis, theoretical machine learning on networks, and high-dimensional statistics. Key Responsibilities: Take the lead in developing sub-projects (problem formulation
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are expected to submit a career development plan, specifying career goals and the competencies that the PhD fellow should acquire, no later than one month after commencement of the fellowship period. The
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, output validation and reporting. Developing integrative strategies for a diverse set of data, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning
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of the project in top tier conferences and journals Key Competencies and Requirements: PhD in Electrical and Electronic Engineering/Computer Engineering/Computer Science or related engineering degree At least 1
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investigators to acquire essential academic credentials and research skills with the purpose of increasing competitiveness for MD, PhD, or MD-PhD programs in biomedical sciences. Primary Responsibilities Devote
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, develop research proposals and attract additional external fundings when appropriate. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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mechanics, data-driven approaches, and machine-learned interatomic potentials are highly beneficial but not required. We offer The 3-year Liebig PhD Fellowship is tax-free and is funded 1850 euros/month. The
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engineering (elkraft). Experience in cybersecurity incident management. Experience in machine learning/artificial intelligence methods. Experience in simulation and modeling. Applicants will be assessed