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We describe a project-based computational physics course developed using a backwards course design approach. From an initial competency-based model of problem solving in computational physics, we interviewed faculty who use these tools in their own research to determine indicators of expert practice. From these, a rubric was formulated that enabled us to design a course intended to allow students to learn these skills. We also report an initial implementation of the course and, by having the interviewees regrade student work, show that students acquired many of the expert practices identified.

Non-spherical emulsion droplets can be stabilized by densely packed colloidal particles adsorbed at their surface. In order to understand the microstructure of these surface packings, the ordering of hard spheres on ellipsoidal surfaces is determined through large scale computer simulations. Defects in the packing are shown generically to occur most often in regions of strong curvature; however, the relationship between defects and curvature is nontrivial, and the distribution of defects shows secondary maxima for ellipsoids of sufficiently high aspect ratio. As with packings on spherical surfaces, additional defects beyond those required by topology are observed as chains or "scars". The transition point, however, is found to be softened by the anisotropic curvature which also partially orients the scars. A rich library of symmetric commensurate packings are identified for low particle number. We verify experimentally that ellipsoidal droplets of varying aspect ratio can be arrested by surface-adsorbed colloids.