Postdoctoral Researcher in AI Modeling of Cellular Dynamics, Alpha Cell Program

Karolinska Institutet; Solna kommun; On-site; SEK 535,680 - 669,600; Full time

Benefits offered by this job

Creative and inspiring work environment

Collaboration with leading experts

Health care provider relationships for groundbreaking research

Job summary

Karolinska Institutet is seeking a postdoctoral researcher for the Alpha Cell program in Solna. The role focuses on developing AI models to understand cellular dynamics, emphasizing scalable neural network architectures.

Applicants should have a PhD in relevant fields, strong programming skills in Python, and the ability to work in an interdisciplinary environment. The position offers method development independence and fosters collaboration across diverse disciplines within a leading medical university.

Qualifications

• PhD in a field such as physics, systems biology, applied mathematics, or machine learning.
• Strong programming skills, particularly in Python and experience with ML frameworks.
• Experience with complex or high-dimensional systems.
• Familiarity with biological data like imaging and proteomics.

Responsibilities

• Develop next-generation AI models of cellular dynamics.
• Integrate spatial imaging data with molecular measurements.
• Implement methods for large-scale molecular imaging and modeling.

Skills

Strong programming skills (e.g. Python)

Experience with modern ML frameworks

Ability to conduct independent research

Experience with complex or high-dimensional systems

Proficiency in written and spoken English

Experience with physics-informed machine learning

Experience with dynamical systems

Background in multiscale modeling

Education

PhD in related fields

Job description

Overview

Alpha Cell is a new SciLifeLab strategic program aimed at building the first molecular-level computational model of the human cell. The program is led by Jan Ellenberg, Director of SciLifeLab and Mathias Ulhen, Director of the Human Protein Atlas, together with a collaborative, multi-institutional constellation of SciLifeLab researchers and infrastructure units. This position is embedded in Avlant Nilsson’s research group at Karolinska Institutet and SciLifeLab. Our lab develops deep learning models of molecular networks in cancer to advance precision medicine by integrating high-throughput data (e.g. transcriptomics, proteomics, metabolomics) with prior knowledge of molecular interactions to construct interpretable models that capture system-level mechanisms in cells to enable the identification of drug targets, biomarkers, and resistance mechanisms.

The project is carried out in close collaboration with Wei Ouyang’s AICell Lab Lab at KTH and SciLifeLab, and the Human Protein Atlas, and has access to state-of-the-art computational infrastructure, including the Berzelius supercomputer.

Responsibilities

The emphasis of the position is method development. We are seeking a postdoctoral researcher to develop next-generation AI models of cellular dynamics, with a focus on scalable neural network architectures that represent the molecular composition of a single cell in space and time. These models will describe high-dimensional systems with many interacting components and may use multiscale and coarse-grained representations to enable scalability.

The work will draw on concepts from dynamical systems, stochastic processes, and stochastic differential equations (SDEs), including nonequilibrium systems, to model cellular behavior. A central goal is to integrate spatial imaging data with time-resolved molecular measurements, while incorporating physical and biological constraints directly into the model architectures. The developed methods will form the foundation for future large-scale molecular imaging and modeling efforts within Alpha Cell. The position offers substantial methodological independence.

Qualifications

Required qualifications:

• PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields.
• Strong programming skills (e.g. Python) and experience with modern ML frameworks.
• Ability to conduct independent research and collaborate in an interdisciplinary environment.
• Proficiency in written and spoken English.
• Experience working with complex or high-dimensional systems.
• Experience with physics-informed or constraint-based machine learning (e.g. neural ODEs, energy-based models)
• Experience with dynamical systems, stochastic processes, or SDEs
• Background in multiscale modeling, coarse-graining, or non-equilibrium systems
• Experience with generative modeling or partially observed systems.
• Familiarity with biological data (e.g. imaging, proteomics, single-cell data)

Prior biological experience is not required. We particularly encourage applicants from quantitative disciplines.

Our lab values diversity and inclusion and strives to create an environment where all individuals can contribute and thrive.

What we offer

A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading medical universities. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. It is the crossover collaborations, which have pushed KI to where it is today, at the forefront of global research. Several of the people you meet in healthcare are educated at KI. A close relationship with the health care providers is important for creating groundbreaking top quality education and research. Karolinska Institutet is also a state university, which entitles you to several benefits through our collective agreement.

Location: Solna

Application

Applications must include documents in English or Swedish:

• PhD certificate
• A complete resumé, including date of the thesis defence, title of the thesis, previous academic positions, academic title, current position, academic distinctions, and committee work
• A complete list of publications
• A summary of current work (no more than one page)

The application is to be submitted through the Varbi recruitment system.