Postdoc position in automatic control with focus on pharmacometric modeling - Hiring in process/Finished, not possible to apply

Do you want to be part of a research environment committed to address data-driven modelling challenges to advance precision medicine? Then this postdoctoral position is aimed for you! Both mathematically oriented candidates, pharmacometry specialists and researchers from backgrounds within data-driven modeling, or neighboring applications of scientific machine learning, are welcome and encouraged to apply.

This position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more: https://wasp-sweden.org/

The focus of the post-doctoral project is development of novel methods for pharmacometric covariate modeling: Given a dynamic drug response model, we are facing the problem of determining its parameters from individual covariates such age, sex, or more generally biomarkers or genetic data.  Apart from extrapolating well, the learned mapping from covariates to parameters should ideally be transparent and explainable. One way to achieve this, which we aim to pursue in the project, is to develop symbolic regression methods that output human-readable formulas. Large pharmacological data sets will be used from day one to ensure practical relevance of the developed methods.

This call is for a postdoc within WASP at Lund University. There will be a twinned postdoc position within DDLS at Uppsala University. The project involves close collaboration between the two postdocs. The Lund position will have a stronger focus on novel method development; the project in Uppsala will have a stronger application focus.

Work duties
The main duties involved in a post-doctoral position is to conduct research. Within this project, you will be working closely together with senior researchers and one or several PhD students at Lund University department of Automatic Control, and collaborate with medical researchers at the department of Pharmacology at Uppsala University. Another assignment is to contribute to the general scientific discussion at the department of Automatic Control.

We encourage our postdocs to gain lecturing experience through teaching PhD courses, but up to no more than 20 % of their full-time employment. The position also includes 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.
• Ability to both work independently and to collaborate.
• Willingness and ability to work across disciplinary boundaries.

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.
• Experience and knowledge within data-driven modelling, scientific machine learning, related mathematics and computational tools.
• Practical experience of working with pharmacological, medical, or other data sets for modelling purposes.

Additional assessment criteria:
Ability to communicate science with an emphasis on publications, but also weighing in formats such as oral presentations, videos and lectured targeting experts or a broader audience. Activity on the open-source scene within projects of relevance to this call.

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.

We are looking for a person who is flexible and open, willing to cooperate and contribute to the overall working climate. Other basis of assessment are driving force and independence as well as ability to make new connections, communicate and cooperate with colleagues within and outside academia.

Terms of employment
This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008 or 19 November 2021. (Applied to employments entered into after the entry into force 2022-02-01).

Instructions on how to apply
Applications shall be written in English. Applications should include a cover letter stating the reasons why you are interested in the position and in what way the employment corresponds to your qualifications. The application should also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).