Opportunities

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Data Science and bioinformatics are rapidly-growing and exciting fields of research. The Anderson Lab team welcomes serious-minded researchers who are enthusiastic about pursuing challenging and meaningful research problems. As you consider joining us in our research, here are some things that you should consider carefully:

Contents

Is research for me?

By definition, research means exploring problems where the answers are not known. There will be frustrations, setbacks, and false leads. Seeming breakthroughs must be viewed with caution and skepticism. Scientists-to-be must be prepared to perservere in the face these setbacks. They must be creative, self-motivated, and persistant.

On a very practical note, it is very difficult to accomplish something significant without a significant commitment of time. That doesn't mean you'll have to spend 40 hours a week working on research, but if your schedule does not permit you to devote a minimum of 10 hours a week, then a research project might not be viable at this time. That grim warning aside, if you do decide to undertake an undergraduate research project, then you'll be part of a team of researchers who are committed to helping one another explore interesting and challenging problems.

Why should I pursue research?

Research is a rewarding and exciting endeavor. My goals for my students are to

  • work on interesting and challenging problems,
  • experience the research process and environment,
  • work on a software project that will distinguish them for future employers,
  • and present their work at a national research conference.

Is the Anderson lab for me?

Our research is successful because we work closely with molecular biologists, biochemists, and medical doctors to pursue research that has scientific relevance. While most students are studying and applying computer science, our students are doing that while at the same time learning cellular and molecular biology, biochemistry, genetics, toxicology, pharmacology and other areas of biology relevant to their research. It takes dedication and focus to pursue cross-disciplinary research. Our students value the opportunity to contribute to science beyond the traditional boundaries of computer science and engineering.

Most importantly, our students are expected to have the maturity to identify and pursue their own ideas. We are looking for highly self-motivated and scientifically curious researchers. If you are looking for an advisor that provides step-by-step instruction or a lot of deadlines, the BiRG lab is probably not a good fit for you.

I want to pursue research, how do I get involved?

  1. If you have an interest in data science but you are not sure about joining our research team, you may want to start by taking our Data Science courses: DATA 101 - Introduction to Data Science, DATA 210 - Dataset Organization and Management, and DATA 495 - Data Science Capstone. Please see http://datascience.cofc.edu for more information.
  2. Come to our lab meetings (not being held yet). All serious students are welcome to join us, regardless of your background (or lack of it) in biology. At our meetings we will discuss current research projects, papers from the scientific literature, and fundamental topics in pattern recognition, evolutionary computation, molecular biology, and biochemistry. The time and place of the Anderson Lab meeting will be set sometime at the beginning of each semester.
  3. Pursue an independent study. As you attend the meetings you will find that there are many open research questions that we do not have the time and resources to pursue. If you would like to investigate one of these questions, it may be possible to do it as an independent study topic. If your are interested in pursuing independent research, you should see me.

What is the application process/requirements?

If you are interested in joining the Anderson Lab, your first step is to contact Dr. Paul Anderson to discuss your background and interests. Please bring/e-mail a copy of your unofficial transcript. A minimum GPA of 3.0 is required.

How many hours a week will this commitment take?

I expect each researcher to be able to devote between 10 and 20 hours a week on their investigations; however, it is understood and assumed that at certain times of the semester you will not be able to spend at least 10 hours of time on your research project.

Can I commit for one semester?

Depending on your background... But to be honest, the most success is reached when there is at least one summer available. Ideally, you will have at least two summers left at the College of Charleston.

Undergraduate Research Opportunities

Updated 3-6-2014.

If you are interested in any of the opportunities below, please send me your current transcript and two short paragraphs (>200 words each):

  1. What are your goals after graduation? It is useful to think endpoint and work your way backward. Industry? Graduate school?
  2. How do your interests relate to at least two of the projects below.

Computational Metabolomics Group

The Computational Metabolomics Group is in need of both programmers and researchers. Our main research interest at this point is the development of a revolutionary scientific software for the metabolomics community. This includes algorithms and application development. Our biggest need at the moment is for students looking to get exposure to open source software development and web-application development (HTML5, cloud, Javascript). Development of a cloud-based laboratory management system for browsers, tablet devices, and client applications using Google App Engine and the Google Docs API. This software will designed to support scientific research in the life sciences disciplines by bringing the power of cloud computing to the scientist.

  • Machine Learning, Data Mining, AI, Evolutionary Algorithms
  • Scientific Data Storage, Management, and Analysis System
  • Tablet and Browser Enabled
  • RESTful Web Service interface
  • Google App Engine
  • Google Docs API
  • Python Programming Language Required
  • Knowledge of one or more of the life sciences (e.g., Biology, Chemistry) is a plus, but it is not required
  • Research and software will be presented at a conference and/or as a journal paper

For more information see Computational Metabolomics Group

Charleston Computational Genomics Group and Bioinformatics Research Group

C2G2 is in need of programmers and researchers. This is a very active group with collaborations with MUSC, NOAA, and the HML. This includes algorithm and application development. As part of this project and really all of the projects in the Anderson Lab, you will gain exposure to high performance computing equipment. We have a personal high performance computing cluster with 100 CPU cores, >400 GB of RAM, and 100 TB of disk storage. All projects are open source and research focused, providing a great opportunity to experience both cultures as you mature as a computer scientist, data scientist, or scientist.

  • Machine Learning, AI, Data Mining, Evolutionary Algorithms
  • Scientific Data Storage, Management, and Analysis System
  • Google App Engine
  • Google Docs API
  • Python Programming Language Required
  • Knowledge of one or more of the life sciences (e.g., Biology, Chemistry) is a plus, but it is not required
  • Research and software will be presented at a conference and/or as a journal paper

For more information see Charleston Computational Genomics Group

Data Science Research Group

The Data Science Research Group interacts with all of the above groups. It is made up of individuals who are creating software for a broad range of disciplines including metabolomics, genomics, and bioinformatics. Our major project is currently designed to revolutionize how data science and computer science is taught and practiced. We are very excited about the initial momentum of this project, and we have recently published a paper that you may read here. This is a very active open source project that is perfect for both computer scientists and data scientists.

  • Machine Learning, AI, Data Mining, Evolutionary Algorithms
  • Scientific Data Storage, Management, and Analysis System
  • Google App Engine
  • Google Docs API
  • Python Programming Language Required
  • Research and software will be presented at a conference and/or as a journal paper

For more information see Data Science Research Group

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