This research project investigates bio-like properties and behaviors of non-living, self-organizing, physical systems called dissipative structures. The project aims at identifying core physical principles which underwrite biological capabilities by studying non-living bio-analogues. The primary system we study is an electrically driven dissipative structure (as an example watch the video here: https://www.youtube.com/watch?v=nxoZ0hHN12I).
We braid together concepts from psychology, cognitive science, kinesiology, physics, chemistry, and thermodynamics for a rich interdisciplinary methodology. This project is thus well-suited for undergraduates studying either the life-sciences or the physical sciences, and ideally an interest in both. Our projects for the near future include topics of evolution, learning, and social coordination. As an undergraduate research assistant, you would aid primarily in conducting experiments, as well as potentially designing and building experimental apparatuses. Ideally you will also learn some rudimentary data analysis tools in Matlab, R, or both (programming facility in other languages is also very welcome).
You would receive training to use the experimental systems, aided by a graduate student mentor, as well as a short survey of relevant research articles for conceptual background. Once you have developed some facility with the system, you would begin to run assigned experiments and collect data on your own. You would be expected to coordinate primarily with your graduate student mentor, and secondarily with your faculty mentor. The time-commitment is flexible and negotiable, likely not exceeding 10 hours a week. The assistant position is minimally for a semester, though renewal for future semesters is possible and ideal. The assistantship would begin at the start of the Spring 2020 semester. RAs will receive research course credits as compensation for their work.
Preferred Qualifications (but not required):
– Undergraduate-level physics knowledge (especially Thermodynamics and Electricity & Magnetism)
– Experience with programming languages (ideally Matlab and/or R)
– An interest in conducting future research
– Good, consistent, work ethic
– Genuine interest in the topic (though you don’t need specific knowledge or experience)
– Desire to learn new concepts, experimental methodologies, and analysis tools
How to Apply
Please email Ben De Bari at Benjamin.email@example.com and include a brief description of why you’re applying for this position and an up-to-date resume. Strong applicants will go through a brief interview process with the graduate student (Ben De Bari) and faculty (James Dixon) mentors.
Mentor: James Dixon, Professor, Psychological Sciences
Mentor email: firstname.lastname@example.org