Doctoral Student in Medical Science, AI and Bioinformatics at BKV

Linköpings Universitet · Full-time

Linköping, Sweden

We have the strength of over 50,000 students and staff members. Students who give hope for the future. Staff members who every day contribute to Linköping University tackling today's challenges. Our core values are based on credibility, trust and security. By being brave, thinking freely and doing new things, we create together, through great and small actions, a better future. Welcome to apply for a job with us! We are now seeking a doctoral student in medical science, AI and bioinformatics. Your responsibilities The project aims to develop AI-based foundation models for integrated analysis of single-cell and multi-omics data to better understand how molecular and cellular processes are coordinated between cells, tissues and organ systems in health and disease. You will be responsible for developing and applying advanced methods in AI and bioinformatics to large-scale single-cell and multi-omics data. The project will focus on integrating this data to study cellular and tissue-specific signaling, molecular communication and systemic molecular networks, as well as how these processes change between physiological and disease states. Through this work, you will develop predictive and biologically interpretable models that connect molecular patterns across multiple levels of human biology. The project is at the intersection of artificial intelligence, computational biology, systems medicine and precision health and involves close collaboration with researchers in both computational and biomedical fields. Beyond the project's primary focus, you will have the opportunity to develop related research questions based on your own interests and new results that emerge during the project. You will thereby develop broad expertise in AI and multi-omics analysis and grow as an independent researcher for a future career in academia, biotechnology or data-driven precision medicine. As a doctoral student, you dedicate yourself to your research training and research projects in which you are involved. Your work may also include teaching or participating in other institutional assignments, up to 20 percent of full-time. Your qualifications You have completed a degree at advanced level in AI, bioinformatics, systems biology or a related field, or completed course requirements of at least 240 credits, of which at least 60 credits at advanced level. Alternatively, you have acquired knowledge equivalent in kind in another way. Additionally required: Strong programming ability and strong quantitative skills, especially in Python and/or R. Experience with deep learning, machine learning or analysis of large-scale omics data. High degree of motivation and independence, good problem-solving ability and ability to collaborate in an interdisciplinary research environment. Ability to communicate fluently in English, both orally and in writing. The following qualifications are not a requirement but are particularly meritorious: Experience with foundation models, transformers, generative models or representation learning. Experience with analysis of large-scale single-cell omics data. Experience with integrative analysis of multi-omics data, such as genomics, proteomics or metabolomics. Experience with relevant machine learning frameworks, such as PyTorch, and high-performance computing environments (HPC). Knowledge in molecular and cell biology, systems biology or precision medicine. Your application must also include a research plan describing how your background, skills and research interests make you suitable for the project on AI foundation models for integrated single-cell and multi-omics analysis. Also briefly describe in the research plan a research question or research direction within AI, single-cell biology, multi-omics or systems medicine that you would be interested in exploring during your doctoral studies. Your workplace You will be employed in the research group led by University Lecturer https://liu.se/medarbetare/wenzh16, fellow in the Swedish national program for https://www.scilifelab.se/data-driven. The research group is located at https://liu.se/organisation/liu/bkv/cnb, https://liu.se/organisation/liu/bkv, Linköping University. The research group focuses on integrative multi-omics, the interaction between genetic variation and human phenotypes and the development of AI-driven methods to better understand human biology and diseases and translate this knowledge into data-driven strategies for precision health. About the employment When you are admitted to doctoral training, your employment as a doctoral student will be processed. Read more about each faculty's doctoral training https://liu.se/forskning/forskarutbildning The employment is time-limited to normally four years full-time. Extension of employment up to five years is based on the degree of teaching and institutional assignments. In special cases, further extension may occur. You will be employed initially for one year, and thereafter the employment is renewed for a maximum of two years at a time, based on the achieved study plan. Start date by agreement. Salary and benefits The doctoral student salary is regulated according to a locally agreed salary scale. Read more about benefits for employees https://liu.se/jobba-pa-liu/formaner. Trade union contact persons Information on trade union contact persons, see https://liu.se/jobba-pa-liu/hjalp-for-sokande. Application You apply for this position by clicking the "Apply" button below. Your application must be received by Linköping University no later than 261030. Applications received after the final application deadline will not be considered. We welcome applicants with different backgrounds, experiences and perspectives, which enriches and develops our activities. For us, it is self-evident to safeguard everyone's equal value, rights and opportunities. Read about our work with https://liu.se/artikel/lika-villkor/. We look forward to your application! Linköping University has negotiated agreements and asks us to avoid direct contact from staffing and recruitment companies and sellers of job advertisements.