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Join us for an insightful conversation with Eric, a computational biologist at Moderna who made the leap from wet lab science to data science. In this episode, Eric shares his unconventional journey through biological engineering, revealing why he traded pipettes for Python and what it really takes to succeed in computational biology.We explore the stark differences between academic curiosity-driven research and industry's ROI-focused problems, the true value of a PhD in today's job market, and why understanding lab experiments makes you infinitely more valuable as a bioinformatician. Eric doesn't hold back on AI's role in science—explaining why LLMs hallucinate 100% of the time (they're just correct sometimes) and how to avoid the "illusion of breadth" trap.Whether you're a grad student considering industry, a computational scientist looking to level up, or simply curious about the future of AI in research, this conversation offers practical wisdom on career transitions, essential skills, and why writing clean code matters more than you think.Key Takeaways:Why experiment design beats statistical shortcutsThe critical skills that separate pipeline operators from computational scientistsHow to communicate effectively with lab scientistsWhy you should attempt problems before reaching for AI tools#ComputationalBiology #Bioinformatics #DataScience #PhDLife #CareerTransition #AcademiaToIndustry #MachineLearning #AI #ScienceCareers #BiotechIndustry #PythonProgramming #LifeSciences #ResearchCareers #GradSchool #ScientificComputing #ModernaBiotech #BiomedicalEngineering #CareerAdvice #STEMCareers #BiologyTech
