№ lp_2_1_21543
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This document outlines various deep learning models (ResNet-50, CBAM) and their application in radiomics for survival prediction based on medical imaging.
Year: 2020
Region / City: Not specified
Topic: Deep learning, convolutional neural networks, survival analysis, radiomics
Document type: Scientific article
Institution / Organization: Not specified
Author: He Kaiming, Sanghyun Woo, Zwanenburg A et al.
Target audience: Researchers in machine learning, medical imaging, and survival analysis
Period of validity: Not specified
Approval date: Not specified
Date of changes: Not specified
Price: 8 / 10 USD
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Digital Project Officer – CBAM Transition Manager, DG TAXUD, European Commission (Application deadline: 16/09/2025)
Organization: European Commission
Directorate-General: Directorate-General for Taxation and Customs Union (DG TAXUD)
Directorate: Directorate B – Digital Delivery of Customs & Taxation Policies
Unit: TAXUD.B2 – Architecture and Digital Operation
Job Title: Digital Project Officer – CBAM Transition Manager
Domain: Information Technology
Function Group: FG IV
Contract Type: Contract Agent 3b
Location: Brussels
Application Deadline: 16/09/2025 – 12:00 (Brussels time)
Team Size: 20 staff members (CBAM team)
Directorate Staff: 25 officials supported by approximately 35 IT consultants
Annual Budget: Approximately 65 million EUR
Related Initiative: Carbon Border Adjustment Mechanism (CBAM)
Target Audience: Qualified candidates from EU Member States, including underrepresented Member States
Recruitment Basis: Merit-based selection
Topics: ResNet-50 image-based CBAM