Researcher in machine learning with epidemiological applications - Hiring in process/Finished, not possible to apply

The Computational Biology & Biological Physics group pursues research in the fields of computational biology and machine learning, using a broad set of models and methods, often rooted in statistical and computational physics. In particular, the group develops machine learning techniques for biomedical and healthcare applications, computational models for biomolecular and cell systems, and methods for large-scale analysis of spectroscopic and imaging data on biological processes.

The Computational Biology & Biological Physics group has an opening for a position as a researcher in machine learning with a focus on medical applications, starting in January 2023, or by agreement.

Introduction

The Computational Biology & Biological Physics group is engaged in a number of cross-disciplinary projects where machine learning methods are being developed for applications within the healthcare sector. The recruited researcher will in particular be involved in projects where machine learning methods are applied to data from the Swedish register infrastructure to increase the quality and efficiency of healthcare. The proposed solution is based on machine learning using electronic health records (including electrocardiograms) and extensive health care registers. The project includes partners from both other faculties and healthcare providers.

Work duties

The successful candidate will work with heterogeneous databases and pre-processing of medical data, and develop machine learning models, in part based on deep learning techniques, for diagnostic and predictive purposes. The projects are truly cross-disciplinary and will be conducted in close collaboration with experts in areas such as emergency medicine, IT, epidemiology, statistics and language technology. Scientific results are expected to be published in peer-reviewed research journals and high-quality conferences.

Qualifications

The applicant must hold a doctoral degree in machine learning, applied mathematics, computer science, or another relevant field. 

Further mandatory requirements:

• Solid programming experience, including the use of the Python programming language, is a prerequisite.
• Experience in machine learning for medical applications is a prerequisite.
• Good knowledge of English is a prerequisite.

Skills and experience regarded as advantageous:

• Experience in language technology, in particular information extraction from texts.
• Experience of working with health data, including electrocardiograms
• Experience with machine learning in multiple domains, e.g. text, image, tabulated data, etc.
• Experience in system administration for Linux.
• Experience of working interdisciplinarity.
• Good knowledge of the Swedish language.

Terms of employment

Full time permanent position starting in January 2023, or by agreement.

Application procedure

Applications should consist of a CV, a publication list and a short description of current research (max 1 page).

Contact

Professor Mattias Ohlsson, +46 46 2227782, mattias@thep.lu.se