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In education, student teams are composed aiming at completing academic tasks and co-learning. Key factors influencing team performance are individual competencies, personality and gender. In this paper, we present a computational model to compose proficient and congenial teams based on students' personalities, gender, and competencies to perform tasks of different nature. Our model, called synergistic team composition, extends Wilde's post-Jungian method, which solely employs individuals' personalities and gender. In addition to formally present the synergistic team composition problem, we develop an approximate algorithm to solve it. That is, an algorithm that partitions student groups into teams that are diverse in competencies, personality and gender. Finally, we discuss our positive empirical results on student performance.