PhD student in Deep Learning and Mass Spectrometry for Precision Medicine in MS

PhD student in Deep Learning and Mass Spectrometry for Precision Medicine in Multiple Sclerosis

Are you interested in working with the future of precision medicine in multiple sclerosis, with the support of competent and friendly colleagues in an international environment? Would you like to work alongside skilled, supportive colleagues in an international setting, at a university that values sustainability and offers excellent working conditions? If so, we invite you to apply for a PhD position at Uppsala University.

The Department of Medical Sciences is one of the largest clinical departments at Uppsala University, with approximately 250 employees and over 900 affiliated researchers connected through Uppsala University Hospital. Our research spans a broad spectrum of medical fields, closely integrated with clinical activities, and includes both fundamental studies and the development of new diagnostic and therapeutic approaches. Learn more about us at www.medsci.uu.se.

We are looking for a highly motivated and talented candidate for a PhD position in artificial intelligence, deep learning, bioinformatics, and associated data science, to join the research group of Associate Professor Kim Kultima at Uppsala University. This position offers a unique opportunity to contribute to interdisciplinary research at the intersection of AI, systems medicine, and clinical translation. Please read more about our research here.

Duties
The project aims to develop and apply advanced deep learning methods to analyze high-resolution mass spectrometry data in relation to multiple sclerosis (MS), a complex immune-mediated disease characterized by considerable variation in disease progression and treatment response. The goal is to enhance individualized patient stratification and support data-driven therapeutic decision-making.

As a PhD student, you will work on integrated analysis of small-molecule profiles generated by mass spectrometry, combined with electronic health records, genetic data, lifestyle factors, and clinical variables. The focus is on developing deep learning models to manage and integrate these heterogeneous biomedical data.

You will be part of an interdisciplinary and collaborative research environment, working closely with bioinformaticians, analytical chemists, mass spectrometry experts, and clinical researchers. The Kultima group has strong expertise in mass spectrometry, exposomics, and AI-based biomarker discovery. The project is carried out in close collaboration with the Spjuth group (AI and predictive modeling) and the Burman group (clinical MS research). Our latest findings have been published in leading journals such as Nature Communications, BMC Medicine, and npj Digital Medicine. You can also read more in our latest press release here.

The project is funded by the Swedish Research Council, FORMAS, the Marianne and Marcus Wallenberg Foundation, and the Swedish Society for Medical Research (SSMF), ensuring access to state-of-the-art laboratory infrastructure, high-performance computing resources, and a robust research network.

As a PhD student, your primary focus will be on your doctoral studies. Up to 20% of the position may include departmental duties such as teaching or administrative tasks. The standard duration of the doctoral program is four years full-time, extendable to five years with departmental service.

Requirements

• - Eligibility for admission to doctoral studies requires a Master´s/Science degree in engineering, bioinformatics, data science, mathematics, or a closely related discipline.
  
  
• - Alternatively, candidates must have completed at least 240 higher education credits, including 60 at the advanced level, and an independent project of at least 15 credits.
  
  
• - Or, has acquired substantially equivalent knowledge through other means.

Documented experience in data science, R, and/or Python scripting, and statistical or bioinformatics analysis of omics data is required. The successful candidate should demonstrate excellent communication skills and a willingness to collaborate closely with team members, including experimentalists, bioinformaticians, healthcare professionals, and AI/ML researchers. Proficiency in both spoken and written English is essential. Strong references from previous supervisors or instructors are also required. Candidates expecting to complete their degree by spring 2025 are also welcome to apply.

We place great emphasis on personal suitability. Consideration will be given to the candidate’s collaborative ability and initiative, as well as how their background and skills are expected to complement and strengthen the research group’s activities and future development.

Additional qualifications
Previous experience with high-performance computing (HPC) or cloud-based platforms for processing and analyzing large-scale data, and documented expertise in machine learning and biostatistics are substantial merits. A thesis project in bioinformatics, deep learning, or AI, along with documented experience in large-scale data analysis, is highly desirable. Experience working with various types of omics data (such as metabolomics, proteomics, or transcriptomics) is also valuable. Applicants should also have excellent communication skills and the ability to work independently and in multidisciplinary teams. Fluency in spoken and written English is required; Swedish is considered a merit due to some teaching responsibilities. Positive academic references are mandatory.

Your application should include: a cover letter outlining your background, research interests, and motivation (max 1 page); a CV; a summary of your academic qualifications; a copy of your Master's diploma and transcript; a copy of your Master's thesis; contact details for at least two academic references; and any relevant publications.

We look forward to receiving your application and welcoming you to our research team.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100%. Starting date as agreed. Placement: Uppsala

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

For further information about the position, please contact Associate Professor Kim Kultima at kim.kultima@medsci.uu.se.

Please submit your application by June 19th 2025, UFV-PA 2025/1773.

Are you considering moving to Sweden to work at Uppsala University? Find out more about what it´s like to work and live in Sweden.