In this program you will:

• Plan and execute wet lab and/or computational experiments as part of the team and independently.
• Participate in cutting edge research with your team under your PI’s supervision.
• Select research topics collaboratively with your team, in alignment with both your program goals and Retro’s mission.
• Foster collaboration with other internal groups, including Computational Biology, Automation, Animal Facilities, and Operations, to drive research progress.
• Produce extensive studies, publish and present your results at relevant conferences.  
• Write a thesis of at least 20,000 words, as well as at least 3 papers of publishable quality.
• Conduct formal oral thesis defense before your thesis committee.
• Lean into the immersive experience. This may mean experiments by day, writing in the evenings, and/or feeding cells/training models on the weekends. It will definitely mean a huge opportunity for learning, mentorship, and personal and professional growth.
• Meet growth expectations and milestones of progressive independence and by the end of the program have developed into an independent scientist. 

General Program Qualifications:

• STEM MS or a BS. BS must have additional experience. This is a European-style PhD program that does not start off with intro classes like an American PhD; you need to hit the ground running.
• Proven ability to drive things to completion by yourself and in the team; highly self-motivated to make progress on research and writing.
• Demonstrated organizational skills, time management, and attention to detail.
• A budding passion for research on aging and age-related diseases.
• Ability to present your science clearly and concisely and excellent scientific writing skills. 

Applied AI Program Qualifications:

• Demonstrated enthusiasm about mathematics, modeling, algorithms and/or other computational approaches. 
• Proven interest in implementing, improving, and developing new ways to make use of data and models.
• Have experienced a eureka moment, for example by converting raw data (literature, databases, data collection, preprocessing and/or analysis, etc.) into a personally exciting discovery (showcased by projects, software, papers, presentations, etc.).
• Fluency in Python and PyTorch — enough to get to the result while keeping code/pipelines reasonably clean, readable, reproducible, adaptive, etc.
• Eagerness to always improve software engineering, modeling, algorithmic, data practices in a science-heavy environment.
• Genuine excitement about learning, applying, and developing modern AI approaches for advancement of biomedical research in a dynamic, cross-disciplinary and fast-paced scientific environment.