My name is David Angeles Albores (for science purposes, David Angeles-Albores), a computational biologist with expertise in ML/AI and anything genomics. I'm a Python lover, will program in R if you want me to, and my nightmares are haunted by my time in undergrad spent learning MatLab (shudder). I trained as a developmental and molecular biologist before transitioning into full-time computational work. Big fan of open-source code, documentation and fun projects. I like to play in teams. Mexican native, photography lover, and #teamwilpers Peloton fan.

• 💜 Kind people are my people
• 💻👨‍🔬 Computational biology is awesome
• ✨ Love learning
• 🏋️ 🧗🚴🏊 Weight-lifter, amateur climber, cyclist, and swimmer
• 🏃 Ha, just kidding. I do not run. At all. If a bear was chasing us, you would most likely survive.
• 🦭 My spirit animal is the seal. Floppy on land, powerful in the sea... and probably would get eaten by an orca 🤔

I am principally interested in roles where I can bridge computation and biology. I live in the middle of these two fields. I love math, and have significant background in AI/ML, but you can definitely find better AI/ML specialists. I have a pretty deep knowledge of bioinformatics and genomics, with a specific focus on transcriptomics, but I am not the right person to build many of the tools I use daily (all hail Heng Li and Rob Patro and so many others in the open-source compbio community!). And I have an entire PhD's worth of experience with CRISPR, genetic crosses, PCRs, RNA library preps, hypoxia, you name it.

As a result, I tend to carve out a niche as a science translater in teams where you may already have two fantastic experts who really want to work with each other but who are struggling to collaborate because they do not speak the same scientific languages. Some of my past achievements as a science translater have included:

• Development of a pig kidney that was transplanted into a patient with end-stage renal disease! Featured in the New York Times
• Characterization of the effects that minute pheromone exposures have on egg-laying nematodes
• Development of computational methods for the analysis of microbial RNA samples
• Most recently, lots of work developing AI frameworks to carry out new experiments, and conceptual/computational frameworks to interpret the output results
• Computational studies of the integrated stress response

In summary, I feel very lucky to have worked on many different species and many different types of problems across my career. I am a handy programmer, love to solve problems, and am a big believer that encouraging groups to communicate correctly potentiates results.

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