STEM Deep Dive

STEM Deep Dive

Collaborate 1-on-1 with a mentor from ETH Zurich or EPFL on a mini research project in a field like robotics, architecture, or AI. Build hands-on experience in research and innovation, sharpen your problem-solving skills, and gain recognition for your work through curated academic mentorship.

One-on-One Mentorship
Age:  
13+
Duration:  
8 weeks
Format:  
Remote/Hybrid
Dates:  
Flexible
Price:  
CHF 3,000.00
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About the Course

Join us for an exciting collaborative event where students have the unique opportunity to partner 1-on-1 with a mentor from ETH Zurich/EPFL to work on a mini research project in their passion area, such as neuroscience, robotics, artificial intelligence, and more. This hands-on experience allows students to develop their research, critical thinking, and problem-solving skills, all under the guidance of accomplished mentors.

Course Content

Program Highlights:

  • Ongoing 1-on-1 mentorship with experts from ETH Zurich/EPFL
  • Continuous development of critical thinking and analytical skills
  • Opportunities for networking with peers and professionals
  • Encouragement to explore creative solutions and innovative approaches within projects
  • Hands-on experience in chosen research areas (e.g., neuroscience, robotics, artificial intelligence)

Example Weekly Schedule:

Week 1: Program Orientation and Mentor Pairing

  • Introduction to mentors and mentees
  • Discuss research project goals and areas of focus
  • Schedule initial 1-on-1 mentorship meeting

Week 2: Research Project Planning and Skill Development

  • Define research questions and objectives for mini research projects
  • Begin literature review
  • Set milestones and goals

Week 3: Literature Review and Initial Research

  • Continue literature review
  • Initial data collection and analysis
  • Regular mentorship meeting (1-on-1)

Week 4: Progress Assessment and Research Skills

  • Review and discuss project progress with mentor
  • Adjust the research plan if necessary
  • Continue data collection and analysis

Week 5: Experimentation and Data Analysis

  • Conduct experiments or simulations for mini research projects
  • Collect and analyze data

Week 6: Refinement

  • Refine research methodology
  • Analyze and interpret results

Week 7: Expert Insights and Presentation Prep

  • Develop presentation materials for final presentation
  • Rehearse presentation with mentor (1-on-1)

Week 8: Program Conclusion

  • Presentation of results
  • Reflection on personal growth and future research aspirations
  • Distribute certificates of completion