Research Assistant - (Mal)Adaptive Message Passing in Natural and Artificial Intelligence

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Research assistant (fixed-term contract) – (Mal)adaptive Message Passing in Natural and Artificial Intelligence at Aarhus University  

The research project (Mal)adaptive Message Passing in Natural and Artificial Intelligence, funded by the Aarhus University Research Foundation AUFF and affiliated with the Interacting Minds Centre, School of Culture and Society, Aarhus University, is looking to recruit a full-time ( hours/week) research assistant for the period September – August .

Place of employment: Nobelparken, Jens Chr. Skous Vej, 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 contribute to experimental design, data collection, theory development, computer programming, and manuscript drafting related to the project’s main research aim (development and validation of multivariate HGF applications in computational psychiatry). Tasks also include:

  • Data management and analysis
  • Facilitating processes in connection with funding applications
  • Reporting to funding agencies
  • Training student helpers
  • Data collection
  • Establishing collaborations with psychiatric clinical groups.
  • Qualifications

    Applicants are expected to document the following qualifications:

  • Master’s degree in cognitive science, biomedical engineering, or a related discipline (minimum requirement)
  • Familiarity with hierarchical Gaussian filtering
  • Familiarity with and ideally past contributions to the field of computational psychiatry
  • Experience in working with and collecting data from patients with psychiatric disorders
  • Proficiency in the programming languages Julia and Matlab
  • Computational literacy at a high level, including knowledge of data science, data management, and data analysis
  • A professional level of English(spoken and written)
  • Excellent attention to detail
  • A methodological and structured approach to work and good organisational skills
  • Good time-management skills and the ability to meet deadlines
  • Good interpersonal and collaborative skills
  • Applicants who can document experience gained in similar roles will have an advantage, but this is not a requirement.

    The application must be uploaded in English.

    Further information

    About the position, please contact Associate Professor Chris Mathys (). 

    About applications, please contact HR supporter Gerd Cecilie Bech Thomsen ().

    About the project

    The project (Mal)adaptive Message Passing in Natural and Artificial Intelligence aims to describe quantitatively how people come to believe that unrelated things are related. This will allow new insights into the emergence of maladaptive beliefs such as delusions or the distorted views of others which are typical for example in borderline personality disorder. 

    The quantitative description the project aims for is based on the modelling framework of hierarchical Gaussian filtering. The hierarchical Gaussian filter (HGF) class of models (Mathys, et al., ; ) can be used to describe mental processes as networks of nodes which pass messages among each other, similar to artificial neural networks (ANNs). In doing this, it links natural and artificial intelligence. 

    A key advantage of HGFs is their ability to describe the (conscious or unconscious) beliefs that guide decision-making under uncertainty. HGFs describe the uncertainty of beliefs and not only their content. (Mal)adaptive Message Passing in Natural and Artificial Intelligence aims to take this to the next level. 

    Deadline: May

    Skriv i din ansøgning, at du fandt jobbet på ofir.dk


    Research Assistant - (Mal)Adaptive Message Passing in Natural and Artificial Intelligence

    Research assistant (fixed-term contract) – (Mal)adaptive Message Passing in Natural and Artificial Intelligence at Aarhus University  

    The research project (Mal)adaptive Message Passing in Natural and Artificial Intelligence, funded by the Aarhus University Research Foundation AUFF and affiliated with the Interacting Minds Centre, School of Culture and Society, Aarhus University, is looking to recruit a full-time ( hours/week) research assistant for the period September – August .

    Place of employment: Nobelparken, Jens Chr. Skous Vej, 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 contribute to experimental design, data collection, theory development, computer programming, and manuscript drafting related to the project’s main research aim (development and validation of multivariate HGF applications in computational psychiatry). Tasks also include:

  • Data management and analysis
  • Facilitating processes in connection with funding applications
  • Reporting to funding agencies
  • Training student helpers
  • Data collection
  • Establishing collaborations with psychiatric clinical groups.
  • Qualifications

    Applicants are expected to document the following qualifications:

  • Master’s degree in cognitive science, biomedical engineering, or a related discipline (minimum requirement)
  • Familiarity with hierarchical Gaussian filtering
  • Familiarity with and ideally past contributions to the field of computational psychiatry
  • Experience in working with and collecting data from patients with psychiatric disorders
  • Proficiency in the programming languages Julia and Matlab
  • Computational literacy at a high level, including knowledge of data science, data management, and data analysis
  • A professional level of English(spoken and written)
  • Excellent attention to detail
  • A methodological and structured approach to work and good organisational skills
  • Good time-management skills and the ability to meet deadlines
  • Good interpersonal and collaborative skills
  • Applicants who can document experience gained in similar roles will have an advantage, but this is not a requirement.

    The application must be uploaded in English.

    Further information

    About the position, please contact Associate Professor Chris Mathys (). 

    About applications, please contact HR supporter Gerd Cecilie Bech Thomsen ().

    About the project

    The project (Mal)adaptive Message Passing in Natural and Artificial Intelligence aims to describe quantitatively how people come to believe that unrelated things are related. This will allow new insights into the emergence of maladaptive beliefs such as delusions or the distorted views of others which are typical for example in borderline personality disorder. 

    The quantitative description the project aims for is based on the modelling framework of hierarchical Gaussian filtering. The hierarchical Gaussian filter (HGF) class of models (Mathys, et al., ; ) can be used to describe mental processes as networks of nodes which pass messages among each other, similar to artificial neural networks (ANNs). In doing this, it links natural and artificial intelligence. 

    A key advantage of HGFs is their ability to describe the (conscious or unconscious) beliefs that guide decision-making under uncertainty. HGFs describe the uncertainty of beliefs and not only their content. (Mal)adaptive Message Passing in Natural and Artificial Intelligence aims to take this to the next level. 

    Deadline: May

    Skriv i din ansøgning, at du fandt jobbet på ofir.dk


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