End-of-studies internship focused on developing digital solutions for transportation management, mobile security robots, KPI automation, SAP QM knowledge platforms, and AI-driven visual management systems.
Responsibilities
Develop a digital solution to automate transportation planning and optimize bus capacity utilization.
Design and develop an autonomous or semi-autonomous rover for industrial site surveillance.
Design and develop an intelligent platform to automate KPI collection, validation, reporting, and analysis.
Build a centralized SAP QM knowledge and lessons learned platform using Power Apps.
Design an AI-based visual management tool for efficient projects tracking and decision-making.
Requirements
Final-year Engineering Student in: Data Science, Industrial Engineering, Information Systems, Data Analytics
Final-year Engineering Student in: Data Engineering, Business Intelligence, Data Analytics, Artificial Intelligence, Enterprise Information Systems
Engineering student in Software Engineering, Computer Science, or Industrial IT
Final-year student (Bac+5) in Engineering School or Master's Degree in Industrial Engineering, Project Management, Data Science, Artificial Intelligence, Computer Science, or a related field
Design and facilitate the flow, exchange and interchange of Big Data within the Sharjah Marine Science Research Center, applying FAIR principles and supporting AI/ML integration.
Responsibilities
Create an effective and interconnected SMSRC Data Ecosystem
Design and facilitate the flow, exchange and interchange of Big Data
Envision how the PML data ecosystem could interact with the wider global data ecosystems
Apply FAIR principles to the SMSRC data ecosystem
Facilitate the use of data for scientific discovery
Requirements
Nice to have: Familiarity with marine science and research activities
Nice to have: Flexibility and adaptability
Nice to have: Background in academic or marine research institutions or data centres
Nice to have: Demonstrated interest in the marine environment
Designing and implementing advanced Artificial Intelligence and Data Science solutions, defining scalable AI and Machine Learning architectures, and deploying models into production environments.
Responsibilities
Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements.
Develop, train, validate, optimize, and deploy Machine Learning models into production environments.
Build AI solutions leveraging both traditional Machine Learning algorithms and Large Language Models.
Define reliable data quality, validation, and control mechanisms to support AI initiatives.
Optimize model performance through advanced statistical techniques and hyperparameter tuning.
Requirements
Nice to have: End-to-end AI solutions design
Nice to have: Cloud platform exposure (AWS, Microsoft Azure, GCP)
Nice to have: MLOps practices
Nice to have: Large-scale distributed data environments (Cloudera)
Senior Talent Acquisition Specialist responsible for designing, implementing, and operating a formal recruitment and selection system to attract high-impact talent for commercial and engineering teams.
Responsibilities
Design and improve the Talent Attraction Model (MAT)
Operate and optimize an Applicant Tracking System (ATS)
Utilize AI for filtering, segmentation, and initial candidate contact
Lead the Separation Sciences (SS) Group within the Actinide, Geosciences, and Separation Sciences (AGSS) Theme, shaping a fundamental research program and advancing molecular-level understanding of chemical separations.
Compensation
The expected hiring range for this position is $148,125.00 - $231,075.00.
Responsibilities
Shape and execute the SS Group’s research strategy
Lead and contribute to world-leading, hypothesis-driven research
Sustain a strong fundamental research program while expanding capabilities in emerging areas
Develop competitive research proposals and secure external funding
Build productive relationships with DOE sponsors and program managers
Contribuer au développement de méthodes de génération de bruit en environnement sous-marin, avec un focus particulier sur les vocalises de mammifères marins, en collaboration avec CortAIx Labs.
Compensation
Tous nos stages sont conventionnés et soumis à une gratification dont le montant est déterminé selon votre niveau d’études.
Responsibilities
Définir et mettre en place une méthode générative sur des données acoustiques sous-marines
Sélectionner et mettre en œuvre des simulations sur un cas d’usage
Choisir des métriques d’évaluation de la performance et évaluer les résultats obtenus
Sélectionner et évaluer les paramètres nécessaires à l’étude
Rédiger un rapport d’étude détaillé et présenter les résultats
Requirements
Bac+5 en école d’ingénieur ou en Master 2, à dominante Intelligence Artificielle
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