DDLS industrial PhD student in Data-driven Precision Medicine and Diagnostics

Project: Cross-Species Representation Learning for Translational Disease Insights.

We are looking for an Industrial PhD student in AI/ML to work on a data-driven precision medicine project in collaboration with AstraZeneca (Gothenburg Sweden) and KTH Royal Institute of Technology / SciLifeLab (Stockholm Sweden).

The project: The industrial PhD student will develop AI methods to align and integrate multimodal biomedical data across early discovery in vitro assays in vivo preclinical studies and human clinical biomarker profiles. The work focuses on building shared cross-species representations that capture conserved biological processes and allow diverse measurements such as imaging molecular profiles and standard biomarkers to be interpreted in a unified way. Using existing foundation models as feature extractors and developing lightweight alignment and fusion modules the project will connect signals across modalities and experimental settings even when direct pairing is limited. The overall goal is to improve translational understanding by linking early perturbation signatures to downstream tissue- and organism-level responses and to establish a methodological framework that can be reused across therapeutic areas and study types.

Focus areas of the position: Multimodal representation learning Cross-domain / cross-species alignment Foundation models.

Essential skills and experience:

• Education: MSc (or equivalent) in machine learning computer science engineering applied mathematics physics or a closely related field; candidates with other quantitative backgrounds are welcome.

• Core ML skills: solid foundation in deep learning / representation learning

• Programming and data management: solid programming skills in Python/PyTorch and ability to work with large and/or heterogeneous datasets is expected.

• Communication & collaboration: ability to communicate technical work clearly and collaborate effectively in cross-disciplinary teams.

Desirable skills and experience:

• Background in applying AI to life-science or medical problems and/or familiarity with translational research

• Prior work on multimodal and/or self-supervised learning

The research group: The PhD students time will be split between KTH and AstraZeneca in Gothenburg. At KTH the student will join Kevin Smiths research group at SciLifeLab which develops machine learning methods for biomedical and clinical applications with emphasis on multimodal learning domain adaptation and human-AI collaboration. The groups research focuses on integrating heterogeneous data such as imaging molecular profiles and clinical signals to build models that generalize across diverse settings and support real-world decision-making. The group is highly interdisciplinary works closely with clinical and industrial partners and offers a collaborative environment with strong computational resources.

AstraZeneca is a global science-driven biopharmaceutical company (). We are dedicated to turn ideas into life changing medicines and strive to continuously meet the unmet needs of patients worldwide. At AstraZeneca R&D in Gothenburg we have more than 3000 people from over 50 countries to support generation of new medicines through drug discovery development and clinical trials. Clinical Pharmacology and Safety Sciences (CPSS) provide non-clinical safety clinical pharmacology and quantitative modeling support to the R&D portfolio with expertise in mechanistic discovery safety regulatory toxicology pathology animal sciences clinical pharmacology and pharmacometrics quantitative modeling and data sciences. Our work impacts molecule design selection clinical study design dosing regimens regulatory approval of new medicines and life-cycle management.

KTH Royal Institute of Technology is an international technical university ( focused on innovative cutting-edge research and education. The university offers nearly 100 programs attracting around 17000 students globally. Our programs encourage critical thinking and collaboration to address complex challenges in a changing world. Through partnerships with industry and society students have the opportunity to tackle real-world problems and our interactive and experimental learning environments develop practical professional skills and creativity. The Department of Computational Science and Technology ( is a multidisciplinary field that uses advanced computing methodologies to understand and solve complex problems. The department develops methods computing environments and data analysis capabilities to solve scientific questions in a multi-disciplinary setting shaping the future of computing.

How to apply: The application written in English is submitted through the application portal of AstraZeneca by May 17th and should contain:

• Cover letter in which the applicant motivates their interest for the position and states relevant qualifications.

• CV including at least two references (phone number and email)

• Copies of relevant certificates degrees and grades.

Pay: According to local agreement

Start date: or otherwise agreed.

Type of employment: Temporary position 4 years

Working hours: 100%

Date Posted

Closing Date