Fixed Term Assistant Professor – Mechanisms of Madness: Computationally (De)constructing Delusions

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BEMÆRK: Ansøgningsfristen er overskredet

The School of Culture and Society at Aarhus University invites applications for the position of assistant professor of Computational Cognitive Science based at the Department of Culture, Computation, and Cognition.

The appointment is a full time and fixed-term three-year position. The position begins on 1st May 2024 or as soon as possible thereafter.

Place of employment: Nobelparken, Jens Chr. Skous Vej, 8000 Aarhus C.

The university is keen for its staff to reflect the diversity of society and thus welcomes applications from all qualified applicants, regardless of their personal background.

Members of the academic staff at the School of Culture and Society are expected to contribute to a vibrant, enjoyable and friendly work environment. We emphasise the importance of active participation in the daily life of the department.


The position

The successful applicant is expected to work on theory development and mathematical modelling, computer programming, and manuscript publication related to the project Mechanisms of Madness, which will be conducted at the Interacting Minds Centre during the period of employment. The successful applicant will contribute to the projects main theoretical research aim: developing artificially intelligent agents which navigate environments whose ambiguities can be resolved in realistic as well as in delusional ways. The successful applicant will also be required to teach courses on Aarhus University’s Cognitive Science degree programmes, and Aarhus University’s BA elective in Cultural Data Science. The applicant will also be required to complete Aarhus University’s Pedagogical Program, as part of the Assistant Professorship. Specific tasks include:
 

  • Software development and maintenance for the project
  • Data management and analysis
  • Training student helpers
  • Establishing collaborations with other research groups.
  • Publishing research relating to the project
  • Teaching the course Methods 2: The General Linear Model on the BSc Cognitive Science
  • Teaching the course Introduction to Cultural Data Science on the BA Elective in Cultural Data Science
  • Supervising MSc thesis projects related to the aims of the project


Qualifications

Applicants are expected to document the following qualifications:
  • Doctoral degree or equal qualifications in cognitive science, computer science, mathematics, biomedical engineering, or a related discipline
  • Expertise in computational modelling
  • Proficiency in scientific and statistical programming using e.g Julia, Python, R, and/or Matlab
  • Familiarity with the field of computational psychiatry
  • Experience in data preprocessing, data management and data analysis
  • Teaching experience in cognitive modelling and/or computational methods for cognitive science
  • A professional level of English (spoken and written)
  •  
Finally, applicants are asked to provide a research plan for the next three years as well as their strategy/vision for their contribution to future developments within the field.

The application must be uploaded in English.

Please note that applications that do not include uploaded publications (maximum five) will not be considered.
Although the Aarhus University application system includes an option to upload letters of recommendation, please do not include letters of recommendation or references with the application. Applicants who are invited to an interview may be asked to provide references.

Work environment

Active participation in the daily life of the department is a high priority, and we emphasise the importance of good working relationships, both among colleagues and with our students. In order to maintain and develop the department’s excellent teaching and research environment, the successful applicant is expected to be present at the department on a daily basis.
We respect the balance between work and private life and strive to create a work environment in which that balance can be maintained. You can read more about family and work-life balance in Denmark.
Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU.

International applicants

International applicants are encouraged to read about the attractive working conditions and other benefits of working at Aarhus University and in Denmark, including healthcare, paid holidays and, if relevant, maternity/paternity leave, childcare and schooling. Aarhus University offers a wide variety of services for international researchers and accompanying families, including a relocation service and an AU Expat Partner Programme. You can also find information about the taxation aspects of international researchers’ employment by AU.



Further information

For more information about the position, please contact Associate Professor Chris Mathys (chmathys@cas.au.dk).

For more information about applications, please contact HR supporter Marianne Birn (mbb@au.dk).


About the project

Delusions are an unsolved problem in the mathematical modelling of mental processes. They are defined as false beliefs that are held with absolute conviction and cannot be changed by countervailing evidence. They are particularly difficult to describe formally (i.e., mathematically) because of the tension between the emergence and the maintenance of delusions. While the emergence of a false belief requires jumping to conclusions (being too quick to believe), the maintenance of the same belief requires stubbornly rejecting to form new conclusions (being too slow to believe).

The project Mechanisms of Madness (MoM) makes use of artificial intelligence (AI) to (de)construct architectures of delusional thinking by constructing artificially intelligent agents capable of the same kind of aberrant ‘thinking’ we see in delusional humans.

Mechanisms of Madness builds on a mathematical framework for the study of delusions recently developed in our group. Crucially, this allows artificially intelligent agents to be tuned to produce delusional patterns of aberrant inferences. While this is a step forward, the framework needs to be fleshed out with models that can be used to simulate AI agents negotiating challenging, realistic environments.

In particular, the project will
 
  • Develop artificial environments whose structure needs to be learned by engaging with them in order to resolve ambiguities. Critically, these ambiguities can be resolved in appropriate and realistic ways, reflecting the true structure, as well as in delusional ways.
  • Develop AI agents negotiating these environments, who – depending on how they are tuned – develop realistic or delusional beliefs.
  • Let human participants navigate the same environments and describe their behaviour in terms of a corresponding AI agent with a particular parameter setting. This parameter setting can be seen as a kind of ‘delusionality fingerprint’.

 

Qualification requirements

Applicants should hold a PhD or equivalent academic qualifications.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners: Relocation Services for Professors and Postdocs at Aarhus University (au.dk). Please find more information about entering and working in Denmark here: http://international.au.dk/research/.

Formalities

If nothing else is noted, applications must be submitted in English. Application deadline is at 11.59 pm Danish time (same as Central European Time) on the deadline day.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Shortlists may be prepared with the candidates that have been selected for a detailed academic assessment. A committee set up by the head of school is responsible for selecting the most qualified candidates. See this link for further information about shortlisting at the Faculty of Arts: shortlisting


Faculty of Arts


The Faculty of Arts is one of five main academic areas at Aarhus University.

The faculty contributes to Aarhus University's research, talent development, knowledge exchange and degree programmes.
With its 550 academic staff members, 240 PhD students, 9,500 BA and MA students, and 1,500 students following continuing/further education programmes, the faculty constitutes a strong and diverse research and teaching environment.
The Faculty of Arts consists of the School of Communication and Culture, the School of Culture and Society, the Danish School of Education, and the Centre for Teaching Development and Digital Media. Each of these units has strong academic environments and forms the basis for interdisciplinary research and education.

The faculty's academic environments and degree programmes engage in international collaboration and share the common goal of contributing to the development of knowledge, welfare and culture in interaction with society.

Read more at arts.au.dk/en

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.


Aarhus University

Aarhus University is an academically diverse and research-intensive university with a strong commitment to high-quality research and education and the development of society nationally and globally. The university offers an inspiring research and teaching environment to its 38,000 students (FTEs) and 8,300 employees, and has an annual revenues of EUR 935 million. Learn more at www.international.au.dk/

INFORMATIONER OM STILLINGEN:

- Arbejdspladsen ligger i:

Aarhus Kommune

-Virksomheden tilbyder:

-Arbejdsgiver:

Aarhus Universitet, Jens Chr. Skous Vej 4, 8000 Aarhus C

-Ansøgning:

Ansøgningsfrist: 24-03-2024; - ansøgningsfristen er overskredet

Se mere her: https://job.jobnet.dk/CV/FindWork/Details/6003774

Denne artikel er skrevet af Emilie Bjergegaard og data er automatisk hentet fra eksterne kilder, herunder JobNet.
Kilde: JobNet