Post-doctoral position alternatively researcher position 1+1 years with emphasis on machine learning in the social sciences - Hiring in process/Finished, not possible to apply

Subject description
In today's rapidly evolving world, the intersection of technology and social science presents unprecedented opportunities to address complex societal challenges. We are at a pivotal moment where the power of machine learning (ML) can be harnessed to unlock insights from vast databases, illuminating the intricacies of human life and contributing to a deeper understanding of societal dynamics. Our project aims to be at the forefront of this exciting frontier, leveraging detailed statistical databases to shed light on the multifaceted aspects of people's lives. We are seeking a highly motivated post-doctoral researcher with a passion for innovation and a deep interest in applying machine learning techniques to social sciences related challenges. This unique position is not just about the technical mastery of ML algorithms but also about understanding the social context in which these technologies are applied. The ideal candidate will possess a rare combination of skills - proficiency in machine learning coupled with an appreciation for social science research and its potential to inform policy, drive social change, and improve lives.

Project Description
The overall aim of this project is to develop a groundbreaking social science research instrument and methodology, the Nexus Engine, enabling us to investigate a wide spectrum of inquiries, ranging from pinpointing the pivotal life factors influencing individual trajectories to unveiling latent forces that mold the trajectories of organizations and complex systems. In essence, the Nexus Engine will empower us to explore questions at multiple scales, encompassing the individual, organizational, and systemic dimensions. The Nexus Engine is a project that collates three decades of data from every Swedish individual, creating a living, evolving space-time cube of approximately 8 million life trajectories. From the child born in a remote town who grows up to become a world-renowned inventor, to the city-born individual who decides to break the corporate ladder and embark on an entrepreneurial journey; every story, every interaction, every choice made - is captured.

But the true power of the Nexus Engine lies in its integration with advanced computational analysis techniques. Rather than relying on generic algorithms, we utilize specialized data analytics through machine learning, natural language processing, and statistical modeling to decipher patterns, predict potential, and uncover how hidden intersections between lives affect organizations and systems. It's a deep dive into the core of human capabilities, achievements, and social dynamics.

Why is this important? Because understanding the intricate dance of human lives helps us answer profound questions: What environments foster specific capabilities? How do interactions shape destinies? What are the unknown forces that pull the strings of society?

The research proposed goes far beyond current methods. The Nexus Engine will – like a new telescope – allow us to see further than we have done previously. While education is a relevant proxy for human capabilities, it is incomplete and becomes less relevant as time passes. Using the wealth of information associated with the life history of all individuals on the Swedish labor market will be a game changer for inferring human capabilities.

Work duties
The main duties involved in a post-doctoral position is to conduct research. Teaching and administrative duties are included up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

Qualification requirements 
Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier. 

Additional requirements:
·    Very good oral and written proficiency in English.
·    Good publication records in the area of machine learning and especially autoencoders or transformers. Natural language processing experience is desirable.

The research work will focus on the development of machine learning methods and natural language processing approaches for data and text analysis. The work can entail any and all of the following:
•    ways to identify missing noisy or faulty data;
•    methods for data cleaning and data generation; 
•    application of natural language processing methods;
•    design of improved loss functions and information theory approaches which enhance data analysis of information;
•    design of improved autoencoders (VAEs, GANs), diffusion models and other such machine learning methods towards analysis and detection of features and patterns of a learned probability distribution in latent space. 

Assessment criteria and other qualifications
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.
Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:
·    A good ability to develop and conduct high quality research.
·    Ability to work in research teams and conduct collaborative research.

Additional assessment criteria:
·    Proven experience in collaborating with societal actors (firms, policy makers).
·    Teaching skills.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
The position involves 1+1 years full-time employment.

Instructions on how to apply
Applications shall be written in English and be compiled into a PDF-file containing:

•    résumé/CV, including a list of publications,
  ·    a general description of past research and future research interests, with an explicit reflection how this contributes to achieve the project’s aims (no more than three pages),
  ·    copy of the doctoral degree certificate, and other certificates/grades that you wish to be considered.
  ·    Contact information to two or more references (will be required for candidates invited for interviews).