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Unformatted text preview: Molecular Cell Forum How To Choose a Good Scientific Problem Uri Alon 1 , * 1 Department Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel *Correspondence: firstname.lastname@example.org DOI 10.1016/j.molcel.2009.09.013 Choosing good problems is essential for being a good scientist. But what is a good problem, and how does a scientist choose one? The subject is not usually discussed explicitly within our profession. Scientists are expected to be smart enough to figure it out on their own and through the observation of their teachers. This lack of explicit discussion leaves a vacuum that can lead to approaches such as choosing problems that can give results that merit publication in valued journals, resulting in a job and tenure. The premise of this essay is that a fuller discussion of our topic, including its subjective and emotional aspects, can enrich our science, and our well-being. A good choice means that you can compe- tently discover new knowledge that you find fascinating and that allows self- expression. We will discuss simple principles of choosing scientific problems that have helped me, my students, and many fellow scientists. These principles might form a basis for teaching this subject generally to scientists. Starting Point: Choosing a Problem Is an Act of Nurturing What is the goal of starting a lab? It is sometimes easy to pick up a default value, common in current culture, such as ‘‘The goal of my lab is to publish the maximum number of papers of the high- est quality.’’ However, in this essay, we will frame the goal differently: ‘‘A lab is a nurturing environment that aims to maximize the potential of students as scientists and as human beings.’’ Choices such as these are crucial. From values—even if they are not consciously stated—flow all of the decisions made in the lab, big and small: how the lab looks, when students can take a vacation, and (as we will now discuss) what problems to choose. Within the nurturing lab, we aim to choose a problem for our students (and for ourselves) in order to foster growth and self-motivated research. The Two Dimensions of Problem Choice To choose a scientific problem, let us begin with a simple graph, as a starting point for discussion ( Figure 1 ). We will compare problems by imagining two axes. The first is feasibility —that is, whether a problem is hard or easy, in units such as the expected time to complete the project. This axis is a function of the skills of the researchers and of the technology in the lab. It is important to remember that problems that are easy on paper are often hard in reality, and that problems that are hard on paper are nearly impossible in reality....
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This note was uploaded on 09/12/2011 for the course DPQ 09 taught by Professor Johncarpenter during the Spring '08 term at UFSCar.
- Spring '08