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Field
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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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. Candidate eligibility requirements: Candidates must hold, at the time of application, a bachelor degree Electronics and Computer Engineering or related areas. Candidates must also have knowledge of: i. System
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29 Jun 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Engineering » Biomedical engineering Researcher Profile First Stage Researcher (R1
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contains the skills and knowledge you will acquire Open and inclusive working environment with committed colleagues Mentor programme as a new employee at NTNU Favourable terms in the Norwegian Public
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delivery for company employees and healthcare professionals, contributing to the team's capability-building and knowledge-transfer goals. Role-specific skill focus — MedTech / HealthTech Engineering
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. Candidates should be able to rapidly learn new approaches, work independently, generate publication quality data, and craft the data into manuscripts and fellowship applications. Job Description: Key Roles and
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, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an advantage Familiarity with large biological
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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qualitative experiential data, and mobilise knowledge within mental health systems to inform service improvement. Help mental health services improve the support they offer to people with ongoing and severe
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://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Unsupervised Incremental Representation Learning for Ground-Based Drones in Dynamic Industrial