Teaching & Training

Post-doctoral research position focused on auditing, analyzing, and mitigating bias in 3D facial reconstruction AI systems through data-centric methodologies and statistical analysis.

On-site and remote customer training and support role focused on helping restaurant and retail clients install, configure, and learn to use point-of-sale and digital tools. Mix of hands-on equipment setup, customer education, and troubleshooting.

Support the design, coordination, and delivery of learning and development programs for Sony Music employees, including organizing trainings, workshops, onboarding events, and managing communications around internal L&D initiatives.

Support and grow thinkcell's academic program by handling student/professor requests, coordinating workshops, managing outreach initiatives, and improving processes to expand access to the software at universities worldwide.

A structured training/bootcamp program teaching visual design, video production, audio engineering, and AI tools to career changers. Participants learn industry-standard creative software (Adobe suite, DaVinci Resolve) and apply them to produce multimedia content for digital channels.

An apprenticeship role at Mirakl focused on learning their marketplace platform (Mirakl Connect) and likely supporting customer implementation, integration, or technical enablement rather than core product development.

Develop and coordinate human rights education programs and training initiatives, design educational content and formats, build networks with educational institutions and NGOs, and integrate human rights perspectives into campaigns.

Deliver one-on-one German and English language instruction to skilled professionals (engineers, doctors, IT specialists) transitioning to work in Germany, focusing on professional communication, technical vocabulary, and workplace conversation scenarios.

Lead research projects on AI-driven semantic analysis and reasoning systems, supervise PhD students, design experiments, and publish academic papers—blending technical AI knowledge with research direction-setting and mentorship rather than hands-on coding.

Review and evaluate AI-generated responses to analytical chemistry questions for accuracy and scientific rigor, then provide feedback to improve AI model training. No coding required—purely domain expertise and evaluation work.