The DFG Research Training Group “Statistical Modeling in Psychology” (SMiP) offers

6 Positions (65% TV-L E13, 3 years) for its PhD Program.

The SMiP group is a transregional collaboration of twelve renowned behavioral researchers from five German universities: University of Mannheim, Albert-Ludwigs-University Freiburg, Ruprecht-Karls-University Heidelberg, University of Koblenz-Landau at Landau, and Eberhard Karls University Tübingen. The SMiP group aims to overcome the gap between innovations in statistical modeling and substantive research in psychology. Projects in the SMiP group therefore combine research topics from a relevant area of psychology with current advances in statistical methods.

Participation in the SMiP program includes a PhD project under the supervision of a team of SMiP researchers and a curriculum on advanced statistical models and current directions in psychological research. Applicants should hold a very good research-oriented Master’s degree in psychology and have a strong interest in approaching substantive research questions by means of statistical modeling, which may include applications of existing models to new research questions as well as developments of new statistical models or tools. As the official language of the SMiP group is English, proficiency in English is essential.

PhD projects can be assigned to three thematic areas: (1) cognition and social cognition, (2) motivation and affect, and (3) individual differences.

(1) Examples for statistical modeling in “cognition and social cognition” are models for disentangling encoding, retrieval and judgment processes in memory, or evidence accumulation models of decision making. Models are developed to test and revise substantive cognitive and social-cognitive theories (e.g., processing accounts of priming, dual-process theories of attitudes, theories of social memory).

(2) Research questions in the area of “motivation and affect” refer to affective experiences and affect regulation, work-related processes (e.g., job stressor perceptions, recovery from work), as well as properties of assessment methods (e.g., ambulatory assessment, assessment of sensitive attributes).

(3) PhD Projects on “individual differences” can focus on individual differences in personality and cognition, on the relation between individual differences across different domains (e.g., correlation between personality and cognitive processing strategy), and on the measurement of individual differences with psychometric models (e.g., item response models for different response formats).

The SMiP program starts in October 2021, and it supports and accelerates work on the PhD projects: The program consists of 6 semesters of courses, skill trainings, and workshops instructed by SMiP researchers and other renowned experts in the respective fields. The SMiP group is embedded in an international network of distinguished researchers worldwide and supports visits of PhD candidates to external labs and research groups abroad. Participation in the SMiP program further includes funds for conferences and traveling costs, office space, IT equipment, access to laboratory facilities and access to high-speed computers.

Interested candidates should send the completed SMiP Application Form plus the necessary certificates and documents (see https://www.uni-mannheim.de/smip/application/) to Annette Förster via e-mail to foerster smip.uni-mannheim.de or mail to University of Mannheim, Research Training Group SMiP, B6, 30-32, D-68159 Mannheim, Germany.

The Universities of Freiburg, Heidelberg, Koblenz-Landau, Mannheim, and Tübingen seek to increase the percentage of female scientists. Thus, qualified women are especially encouraged to apply.

The closing date for applications is midnight April 20th, 2021.

 

Please note that confidentiality violations and unauthorized third party access cannot be ruled out when using email communications that are not encrypted.

After the application procedure, applications sent via standard mail will only be sent back if a postpaid envelope is included; otherwise they will be destroyed according to statutory provisions of data privacy law; electronic applications will be deleted.