2 jobs found

The Learning Research and Development Center (LRDC) at the University of Pittsburgh is accepting applications for two Postdoctoral Fellowships in youth development and learning across multiple ecological contexts with an emphasis on diversity, opportunity, and equity. The initial appointment will be two years with the possibility of renewal for a third year. The position involves work on several multi-method longitudinal research projects exploring how sociocultural and psychological factors influence youth of color’s identity development, academic learning, and socioemotional wellbeing during middle childhood and adolescence. The work takes an interdisciplinary approach and applies questions and methods from psychological and developmental science to elementary and secondary school settings. Applicants must have a doctorate and a track record of publication in psychology or education, substantive knowledge and background in the field of developmental psychology, child/adolescent development, or learning science, and excellent academic writing and analytic skills. Expertise is necessary in theory, methods, and research framed by dynamic, relational processes of the positive development of diverse youth (particularly youth who have experienced adversity and challenge), in strength-based approaches to research design and program evaluation. Strong quantitative skills (e.g., HLM, SEM, and growth modeling), or experience with longitudinal datasets or mixed-methods approach are preferred.    The fellow will receive strong mentoring with well-established scholars focused on the demanding aspects of producing high quality scholarship. The fellow will be expected to build a research program by formulating research questions, generating research designs, writing grants, conducting analysis, and writing and presenting findings. To apply for this position, please submit (1) a cover letter describing your research goals and training, including why your background and interests are a good match for the position, (2) Curriculum Vitae, (3) two writing samples, (4) three letters of reference to https://app.education.pitt.edu/employment/postings . The online system will prompt applicants to request three letters of recommendation, directly. Reviews of applications will begin immediately and continue until the position is filled. However, interested applicants are strongly encouraged to submit their application no later than 3/1/2020 . Inquiries may be directed to Dr. Ming-Te Wang, at mtwang@pitt.edu , or Dr. James Huguley, at Huguley@pitt.edu   LRDC is an internationally renowned center with the aim of promoting basic and applied research on learning in its cognitive, neural, social, and motivational aspects and to make research and human development links to formal and informal settings. Pittsburgh is repeatedly voted among “The Most Livable City”, with affordable cost of living and access to a wide array of seasonal recreation opportunities, professional and collegiate athletic events, and a vibrant cultural district.

The Institute for Educational Evaluation at the University of Zurich is accepting applications for a Postdoctoral Researcher in statistical and/or computational methods for modeling intensive longitudinal educational and/or developmental data. The initial appointment (80-100% of full time equivalent) will be two years with the option of renewal for a third year and the possibility of promotion into a tenured contract. The position primarily involves work in the methodological research project “Modeling Developmental Trajectories with Intensive Longitudinal Data from Large-Scale Formative Assessments” funded by the Swiss National Science Foundation (PI: Prof. Dr. Martin Tomasik). It is a full research position with no teaching obligations. Your Responsibilities The successful candidate will collaborate in a team comprising another post-doctoral researcher, a technical research assistant, and up to two doctoral students. Against the backdrop of intensive longitudinal data from a computer-based tool for formative student assessment (see Tomasik, Berger & Moser, 2019, in Frontiers of Education ), the successful candidate will apply and develop methods for modelling intraindividual learning trajectories across different subject domains, investigate patterns of heterogeneity in these trajectories, study the longitudinal dynamics between concepts and content domains, and investigate contextual factors predicting learning trajectories. A significant portion of the working time will be devoted to prepare the results of this modelling for publication in scientific journals and presentation at international conferences. The successful candidate will also be involved in mentoring the doctoral students, organizing methodological workshops, and support the team in programming tasks related to the development and the maintenance of the computer-based tool. Your Qualification Requirements Qualified candidates should be self-driven and highly motivated individuals with an established track record, including first-author publications in top-tier international journals. They should have a very strong statistical and/or computational background in order to successfully develop and evaluate methods in the context of time-series analysis, dynamic structural equation modelling, growth mixture modelling, higher-order graph modelling, time-varying effect modelling and/or other related methods capable of separating between-person and within-person variance in order to study interindividual differences in intraindividual change. A solid knowledge of item response theory, good command of machine learning approaches, and advanced programming skills (e.g., Python, C/C++, MATLAB, Perl) is a strong advantage. The successful candidate should have obtained a doctoral degree in mathematics, statistics, computer science, psychometrics, developmental measurement or educational measurement no longer than seven years ago and bring along some experience – or at least strong interest – in developmental and/or educational research. A good command of English and/or German (as the working languages in the project) is mandatory, familiarity with any of the other national languages (i.e., French and Italian) could be helpful.  Our Offer We offer great working conditions on a unique data set ( N ≈ 100.000) and the opportunity to significantly expand one’s publication record. This interdisciplinary research project is conducted in collaboration with leaders in the field of machine learning, signal processing theory, computational social science, and data analytics. The University of Zurich provides great opportunities for networking within and beyond the Digital Society Initiative (see https://www.dsi.uzh.ch/). The Institute offers an attractive salary plus a very generous social benefits package, five weeks of paid vacation per year, flexible working hours as well as a highly motivated and supportive team of scientific and non-scientific personnel. Application Procedure To apply for this position, please submit in one single PDF file (1) a cover letter describing your past training and your future research goals, highlighting why your background and interests are a good match for the position, (2) a one-page curriculum vitae, (3) a full list of publications, (4) a copy of the doctoral certificate, and (5) three writing samples (i.e., papers published or accepted for publication) to Prof. Dr. Martin Tomasik (martin.tomasik@ibe.uzh.ch). Letters of reference (if available) may be sent directly to Prof. Dr. Martin Tomasik. Review of applications will begin immediately and continue until the position is filled. Interested applicants are strongly encouraged to submit their applications at their earliest convenience but not later than March 31, 2020. Preferred starting date is September 1, 2020. Confidential inquiries concerning this vacancy may either be directed to Prof. Dr. Martin Tomasik or Dr. Laura Helbling (laura.helbling@ibe.uzh.ch). About Us The Institute for Educational Evaluation is a nationally renowned and internationally networked research center associated with the University of Zurich. It is mainly engaged in the field of standardized performance measurement and carries out school effectiveness studies as well as educational surveys and longitudinal studies relevant to education. The IBE also develops software for large-scale adaptive testing and formative assessment (see https://www.mindsteps.ch/) which is implemented in several cantons of Switzerland and also used for research purposes. Located close to downtown Zurich and only seven minutes from the main station, the Institute is perfectly accessible by public transportation. The city of Zurich itself has consecutively been awarded “city with the world's best quality of life” seven times on Mercer research. With its culture, nature and urban-style living, it offers numerous opportunities for leisure and social life.