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Postdoctoral Researcher in Data-Driven Dynamic Modeling

Stockholms Universitet

Stockholms län, Stockholm

Previous experience is desired

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Postdoctoral Researcher in Data-Driven Dynamic Modeling

The Department of Zoology has approximately 80 employees, including researchers, PhD students, and administrative staff.

Research and education at the department take place in an international environment and focus on animal biology. More information about us can be found at: Department of Zoology (https://www.zoologi.su.se).

SciLifeLab is a national research infrastructure located at Campus Solna, where research groups from Stockholm University, KTH Royal Institute of Technology, and Karolinska Institute conduct internationally prominent research in the life sciences.

Project Description

The position will be linked to Assistant Professor Lisandro Milocco's research group at SciLifeLab and the Department of Zoology. Our group focuses on studying various aspects of evolvability – the ability of organisms to evolve. We are interested in developing computational and mathematical tools to understand and quantify evolvability and explore its potential applications.

This project leverages the growing importance of data-driven dynamic modeling – from fluid mechanics to ecosystem studies – to reveal the developmental rules underlying phenotypic variation. The applicants will develop and implement an empirical framework using data-driven algorithms to learn relationships between past and future developmental time points from time series data.

We are seeking up to two highly motivated postdoctoral researchers to work on various aspects of this interdisciplinary project, combining evolutionary developmental biology, dynamic systems, and machine learning.

Responsibilities

The applicants will lead the development and validation of data-driven dynamic models using time series data from developmental pathways. The main tasks include:

  • Developing a data-driven framework for modeling developmental rules. The applicant will implement and evaluate various machine learning algorithms to identify the most effective method concerning prediction accuracy and data requirements.
  • Testing the algorithm with simulated data from various computational models of development, such as models of tooth development and gene regulatory networks.
  • Applying the framework to available experimental data and conducting a meta-analysis.

Eligibility Requirements

A postdoctoral researcher is defined as an employee primarily employed for research who has obtained a doctorate or has a foreign degree deemed equivalent to a doctorate.

Assessment Criteria

The degree must have been obtained no later than when the employment decision is made, but no more than three years before the application deadline. If there are special reasons, the doctorate may have been obtained earlier. Special reasons include leave due to illness, parental leave, trust assignments within trade unions, service in civil defense, or other similar circumstances, as well as clinical service or relevant service/assignments in the subject area.

The doctorate should be in relevant fields of biology (e.g., systems biology, evolutionary biology, developmental biology, computational biology), physics, mathematics, or related fields.

In the appointment, special emphasis will be placed on scientific competence. Expertise in the following three areas will be considered an advantage for the position:

  • Evolutionary and developmental biology: understanding concepts such as developmental bias, developmental constraints, and evolvability; knowledge of methods for automated phenotyping during development (e.g., for gene expression and morphology).
  • Dynamic systems: knowledge of linear and nonlinear theories of dynamic systems, including differential equations, simulation techniques, state space and input-output representations, time delay embedding, and/or time series analysis from experimental data.
  • Machine learning: experience with algorithms such as nearest neighbor, simplex projection, recurrent neural networks, singular value decomposition, and/or autoencoders; experience with frameworks such as TensorFlow or PyTorch.

The selection among qualified candidates will be based on the following criteria:

  • The applicant's documented knowledge and ability to conduct high-quality research in the described area (PhD thesis, publications).
  • Ability for analytical and creative thinking.
  • Enthusiasm, commitment, and the ability to work both independently and in teams.
  • Drive and independence.
  • Good written and oral proficiency in English.

About the Position

The position is full-time and is permanent, but for at least two years and a maximum of three years, with the possibility of extension if there are special reasons. Start date by agreement.

Contact

Inquiries about the position can be made to Lisandro Milocco, lisandro.milocco@zoologi.su.se (mailto:lisandro.milocco@zoologi.su.se).

Application

You apply for the position via Stockholm University's recruitment system. Attach a personal letter describing previous research and future research interests and goals (max. 2 pages) and CV as well as the attachments requested in the application form.

You as an applicant are responsible for ensuring that the application is complete and that it reaches the university by the application deadline.

Instructions for applicants can be found on the webpage: how to apply for a position (https://www.su.se/att-s%C3%B6ka-en-anst%C3%A4llning).

Stockholm University contributes to the development of a sustainable democratic society through knowledge, enlightenment, and the pursuit of truth.

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