We are seeking a talented Data Scientist to join an AI team primarily supporting Group SHE (Safety, Health & Environment) in order to further develop and implement our Sustainability Trajectory Dashboard (STD) Tool.

This innovative project uses agent-based modeling to optimize sustainability investments and accelerate progress toward our environmental targets.

The intern will directly contribute to UNHCR’s coordination of the PROSPECTS Partnership and support engagement with partner agencies and the donor. The intern will be placed within Donor Group VI, located within UNHCR’s Donor Relations and Resource Mobilization Service in the Division of External Relations. However, s/he will support the wider UNHCR PROSPECTS team (Division of External Relations, Division of Resilience & Solutions, Division of International Protection) on a range of administrative, coordination, and communication tasks. The intern may also contribute to supporting wider engagement with government donors within the Donor Group.

The intern’s tasks will include, but will not be limited to:

• Supporting internal coordination and information flow between HQ Divisions, Regional Bureaux and country offices.
• Support preparation, summarising action items and following up on inter-agency meetings and working groups.
• Supporting the preparation of annual Monitoring, Evaluation and Learning Sessions.
• Supporting knowledge management and case study development on PROSPECTS interventions and sustainable responses.

Our Technology Strategy & Transformation team helps clients refresh their enterprise architecture to support the new business direction, and leverages advances in technology areas such as cloud, mobile, digital, and analytics in order to align business strategy and IT.

What will you do:

• Assist the team in their exchange with client top executive as regards how innovation and technology trends such as cloud, analytics, mobile, blockchain and API enable current business and IT imperatives as well as how they will impact their future
• Participate in the design the overall target enterprise architecture including business capabilities, business processes, and business components
• Analyze and compare technology solutions and make recommendations on which solutions are best suited to implement the target enterprise architecture
• Support our clients in their transformation journeys by providing architectural advisory, support to project team.

• Market Insights: Conduct in-depth market research on skincare trends, competitor activities and consumer needs to inform our communication strategies.
• Website Content: Lead the website process for key global NIVEA face care campaigns, ensuring seamless execution and engaging content.
• Cross-Functional Collaboration: Drive key topics with our Legal and R&D departments, ensuring all communications are accurate, compliant and scientifically sound.
• Team Support: Provide support to team members on various face care communication topics, from content creation to social media engagement.

The Vehicle Performance Engineering division (VPE) is part of the R&D group at Toyota Motor Europe Technical Centre in Zaventem, Belgium. Our division is in charge of:

• Identifying market requirements and trends, and turning them into development targets for vehicles, their subsystems, and down to components
• Development of passenger vehicles for the European market
• Researching state of the art and beyond state-of-the-art technologies for implementation in future vehicles.

Inside VPE, the Reliability & Strength team fulfils this role for the Durability, Strength & Operational performance of:

• Vehicle body panels & structures: Engine hood, side doors, luggage door, underbody
• Body functional parts developed in cooperation with our suppliers.      

Your project

The durability & strength performance of car components is one of the basic expectations from our customers. In our search for improving efficiency and reducing the mass of those components, we will conduct the following activity for upper body & closures shell panels development:

Automated prediction process creation and performance robustness confirmation:

• Script development to automate the variation of design parameters to identify the best combination performance-cost-mass
• Development of an automated process for the above
• Make first Proof of Concept to use the obtained results as learning data for a Machine Learning model for durability & strength.