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(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026 Is
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Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country Spain Application Deadline 17 Sep 2025 - 23:59 (Europe/Madrid) Type of Contract Temporary Job Status Part-time Hours Per Week 30
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from the TexNet earth observation program or assets that provide quality data. Compare different methods and tools for deformation modelling. Engage in outside funding activities and promote programs
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Predoctoral researcher at the Targeted Therapeutics & Nanodevices Research Group (Project BRAINZYME)
(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026 Is
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will be working primarily with air quality measurements and analysis of air quality data. The position will focus on indoor and outdoor air quality in relation to children and health. You will be
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7 Nov 2025 Job Information Organisation/Company Universidade de Coimbra Department SGRH - DRGC Research Field Biological sciences » Other Researcher Profile First Stage Researcher (R1) Positions PhD
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methods and data analysis to efficiently generate the right insights. Position within networks, you can effectively gather information and context; you maintain and expand your network for sustainable
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 2 months ago
First Stage Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 14 Oct 2025 - 23:59 (Europe/Lisbon) Type of Contract Not Applicable Job Status Full-time Hours Per Week 40 Offer
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(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Bratislava) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026
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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care