What I’ve Learned in Lab

Hello! My name is Celeste and I was fortunate enough to be selected to participate in EUREKA, a program dedicated to guiding students into undergraduate research at UCSB, as well as aiding them in skills development. I am working in the Kosik lab in the MCDB department and I have really enjoyed my time. I’ve only been in my lab for 3 weeks, but these are a few things I have learned (so far) of what it takes to work in a research lab.

  1. PATIENCE

It takes a TREMENDOUS amount of time and patience to do this kind of work. My project consists of more or less two phases, and the first phase is only just now starting to come to an end. There have been times where reagents are not readily available, a step must be repeated because the results were different from the expected, or a certain procedure might just take an entire day or multiple days. This requires that you not get easily frustrated when things don’t go as planned.

  1. COMING IN ON WEEKENDS

Science is not a 9-5 job, the gears are always turning. I’ve found myself coming in on weekends, even if it is just to do one or two things in the mornings, but the fact that the experiments require constant attention something that aspiring scientists must keep in mind. Even if it means having to cancel on your friends/boyfriend. (Sorry guys!)

  1. PERSISTENCE

I think I have been overwhelmed at times, not necessarily because I’ve needed to do a lot of things, but because it was hard for me to understand exactly why I was doing a certain procedure. This also went along with making sure I was doing the procedures correctly and understanding them when I needed to look back at what I had done. These things are hard to juggle, so it’s important to mentally prepare yourself by taking notes of the processes and reasons why you preformed them, and then constantly look back at them until you truly understand what you’re doing.

  1. CONFIDENCE

The first week in lab, I’m not going to lie, I felt pretty minuscule. There are mainly postdocs and only a few graduate students in the lab group, and I am 1 of only 4 undergraduate students. It was very intimidating at first, going to the ab group meetings and staring at the presenter with awe and confusion, trying to decipher what they were explaining. It honestly still is intimidating, but when you realize they are just people too, they make mistakes, and that at some point, they were in the same position you are in now, it’s easier to feel like you belong.

  1. MISTAKES

Speaking of mistakes, I have made a few and learned that yeah, it doesn’t feel great when you know something went wrong because of you. (Like when cells I split got contaminated… whoops.) But it’s important not to let it get to you and keep trudging forward because nothing great ever came from only perfect runs.

  1. PRACTICE

Lastly, it takes practice to become good at anything. Even those with what you could call “natural talent” practice. I attribute almost all of the things I have accomplished to hard work, and it’s not anything different in the lab.

My (first) Disastrous Night

One of the most important parts of research is making mistakes. This can be terrifying because from the time that we’re young we’re taught that mistakes are a bad thing, so when I messed up almost every part of my first solo reaction, I thought I was done for. I figured that if my mentor didn’t kick me out of lab for the day he would yell at me or be incredibly angry. But none of that happened and I learned a lot. So I’m going to tell my story of my colossal mess up because it’s pretty funny and to show other perfectionists like me that mistakes are okay.

The day started off normal, my mentor was helping me finish working up a reaction that I had set up the previous day and then I started helping him work on his reaction. He asked me to use a machine called a rotovap to evaporate the solvent so that he could see if he made the right thing. I grabbed a flask and started doing what he asked but when he came back in and told me that I grabbed a flask that was wet with water (his reaction was water sensitive). He wasn’t so happy with me after that but he scolded me and got over it. Later, after we finished with everything, he told me that he was going to the office to work on his stuff and he wanted me to work up another reaction that I had done on my own. This was the beginning of a long night.
The first thing I had to do was a simple filtration just so that I could filter away anything I didn’t want (keep in mind this was something I had been doing for months). I grabbed the wrong size funnel and ended up clogging it so what should have been a 2-minute filtration took around an hour. He came in and told me this and essentially said “oh well, start on the next part.” The next part of my work up was washing my solution with salt water and a certain solvent, pretty easy. Well it should have been. I used way too much salt water so it ended up taking me multiple hours and about 6 different Erlenmeyer flasks for one simple wash. But I finally did it and then I had to evaporate the solvent just like I did earlier in the day. I ended up spilling the solvent all over the machine and my mentor had to come in, take it apart, and thoroughly clean it for me.
By the time I was done it was almost 11:30 at night (I started at 6). I jokingly told my mentor that he should find another student and he looked at me, laughed, and said “you’re full of it if you think you’re the only undergrad to ever mess up. This is minor.”
We both left the lab laughing about the day.

First Interests

I knew I wanted to participate in research because I wanted to apply the science I learned in a textbook to a practical use. I have always been a hands-on person, and I knew that by practicing science, I would have a more fulfilling time during my college career. I decided to pursue this interest during the summer before my freshman year. I decided to apply to the CSEP program known as SIMS, the Summer Institute for Mathematics and Science. During this program, I was given a small and brief opportunity to observe and feel what undergraduate research is like. Afterward, I knew that I wanted to continue my undergraduate research experience but I was unsure as to where to begin. I eventually heard about the College of Creative Studies at UCSB. The College of Creative Studies offered their students mentorship under a UCSB faculty member to help and encourage them to enter and flourish in undergraduate research during their college career. After some mentorship from CCS faculty, I decided to look into a research fellowship to further aid me in my search of an undergraduate research lab. After I got accepted into the Early Undergraduate Research and Knowledge Acquisition program, EUREKA, I received additional aid in finding a research lab. Eventually, I found a spot in the Weimb’s lab under the mentorship of Dr. Torres. Now that I have been working in the research lab for several weeks, I hope that I continue to further develop my research and lab skills. During the EUREKA program, I hope to further develop my professional and networking skills. In addition to this, I also hope to become more adept in conducting presentations in a clear, concise, and easy to understand manner. I hope that eventually, I can be a contributing member in the field of science.

The Robot Revolution – Astronomy and Computers

For thousands of years humans have stared at the night sky, naming constellations, telling stories, and making observations about the light of distant stars. Yet, for the majority of that time, astronomers were reliant on what they could glean with their unaided eye. Without a telescope, only about 6,000 stars can be seen from Earth, and from one spot you could only see about a third of those (Bryson).  This is a small fraction of the 1×1024 stars that are estimated to exist. Since the invention of the telescope in the early 1600s, technological advances have gone hand-in-hand with observational astronomy, paving the way for astronomers to look further and create a clearer picture of our universe.

Before this summer, I had thought that observational astronomy consisted of a lone astronomer, or perhaps a team, travelling to be on site with a telescope and staying up all night to adjust the telescopes position and do their observations. Not too long ago, this wasn’t far from the truth. I’d seen images from the Hubble Space Telescope and some other photographs made by professionals and amateurs alike, yet I had no sense of the magnitude of technological advances that had been made in the field.

This summer I began work with the Supernova Group at Las Cumbres Observatory. Amazingly, Las Cumbres Observatory doesn’t actually do any observing on-site. Instead, they manage robotic telescopes around the world that don’t even require a scientist on-site to operate them. This came as a complete shock to me. As far as my role in all of this, I’m not sure quite what I expected, but it certainly wasn’t 8+ hours a day in front of a computer. For interested readers, my daily work schedule looks something like this:

8:30 am: Bike to work

9-5: Work at my computer

5:00 pm: Bike home

Exciting right? The first few days were grueling and frustrating. I had limited experience with programming and working at a computer all day was a big shift from attending classes and doing homework. Yet, the experience has grown on me. It is amazing how much we humans are capable of with a computer at hand.

My current job at the observatory is to create simulations for the new Large Synoptic Survey Telescope (LSST). The LSST will be one of the biggest telescopes in the world, with an aperture of 8.2 meters. (For some suggested names of future large telescopes see https://xkcd.com/1294/) In addition, LSST is completely automated, with preprogrammed directions of where to look during its 10 year survey. The telescope will take in 30 terabytes of data nightly (Lerner). In comparison, the entire NASA data set from 1955 to 2000 consisted of only 1 terabyte. There are not enough scientists in the world to sort through all this data manually (and I’m certainly glad they didn’t just decide to leave this job to the interns).

My goal is to take a known supernovae and pretend that if it were at a certain point in the sky on a certain day of the LSST’s survey. Then, try to answer the question of whether we would be able to find it again. The process of getting this code up and running has been an ordeal during which I’ve learned a lot about programming along with the science behind supernovae and the LSST. In the end I would like to be able to run 100,000 simulations for each kind of supernovae, totaling to nearly a million. Even my computer gets a bit tired out after that kind of task!

Supernova are notoriously difficult to spot, lasting only a short time, and nearly impossible to spot with the naked eye. In 1980, only one or two supernovae were discovered each year. With the advent of advanced telescopes and digital photography to record more than the human eye, this number increased to nearly 200 by 2000. As of 2012, astronomers are finding over 1000 supernovae per year (O’Brien).

Thankfully, with the billions of stars there are out there, astronomers are no strangers to big data. In fact, big data and astronomy have been going steady for a while now. However, we’re still looking for ways to improve how we can store and analyze this excess of data. Sometimes, new technology leads to great improvements in astronomy, and sometimes astronomy must push the advancement of technology.

Sources:

Bryson, Bill. “The Reverend Evans’s Universe.” A Short History of Nearly Everything. New York: Broadway, 2003. 33. Print.

O’Brien, Author Tim. “Supernova 2014J and the Upcoming Deluge of Discoveries.” Professor Tim O’Brien. N.p., 10 May 2014. Web. 08 July 2017.

Lerner, Preston. “July/August 2017.” Discover Magazine. Discover Magazine, 19 July 2011. Web. 08 July 2017.

Why Your Mindset is Important

Most people only really consider a few concrete factors when approaching a task or problem. They might think about how hard or how time-consuming something is, but most miss out on one of the most important aspects; their mindset. Transitioning from high school to college, I realized that I couldn’t just cruise by as easily as I had before; the classes were more difficult and the workload was larger. Later on, when I started working in a lab, I realized that similarly the style of work had changed. Going into lab I knew very little, and I had to learn a lot before I could be productive. During Eureka, one of the workshops we attended, presented by Claire Zedelius, was on the growth mindset. The growth mindset is the idea that talent and ability are gained mostly through experience and training. This is contrasted with the idea of a fixed mindset, which suggests that talent and ability are more fixed and innate. After attending the presentation I realized that I could connect these different mindsets to transitions between high school and college, and to starting research. While it is easy to fall into a fixed mindset over time, it is important to understand that not doing well immediately is not a reflection of your overall ability; rather, it is a sign of the need for more practice and knowledge. Looking back, I’ve realized that whenever I’ve faced a challenge of new content to master, I’ve had to accept that not all concepts and ideas are easy to learn, and that some require lots of work to understand. Difficulty is a natural part of the learning process, and if you constantly find yourself not facing any difficulties, it is a sign that you should push yourself further. This is the attitude I use for my work, and it is with this attitude that I plan to continue my academic career.