North Park University

The Machine Learning for Health team at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our team. Project overview Healthcare systems collect vast amounts of heterogeneous data routinely through interactions with individuals. Our mission is to use machine learning and data science to find better ways to utilize this data in healthcare planning, personalized medicine and targeted recall-studies. In this position, you will be a part of an expanding team working on difficult and meaningful challenges together with clinicians. You get to work with multimodal nationwide Finnish health data from 7 million individuals including for example medication purchases, laboratory measurements, clinical notes and imaging. Your main project will involve building and studying multimodal health trajectories on a nationwide scale to catch increasing disease risk as early as possible. In addition, this data, and similar datasets from our collaborators across the Nordics, Baltics and Europe present a fantastic opportunity to pursue your own ambitious research goals. Our other research directions of interest include privacy of AI models trained on health data as well as training AI models on health data across national borders. Key responsibilities Design, implement and benchmark machine learning models for large-scale health datasets consisting of diverse information including structured medical history, demographics, clinical notes, laboratory measurements, omics and genetics. Collaborate closely with other team members, and national/ international collaborators. Assist other team members in experiment planning, data processing and interpretation of results. Contribute to writing scientific articles, conference presentations, grant applications and supervision of Master’s students and PhD researchers. Take part in open science and code sharing. Skills, expertise and qualifications A PhD degree in computational biology, machine learning, computer science, data science, bioinformatics, or a related discipline Demonstrated machine learning experience in form of high-quality scientific publications, experience working with real-world health data is a plus Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data fusion is highly desirable Ability to work independently, as well as collaboratively in interdisciplinary and international research teams Willingness to supervise junior researchers and develop your supervision skills Excellent command of spoken and written English Research group The Machine Learning for Health team focuses on applying artificial intelligence to derive meaningful insights from large, real-world health and biomedical datasets. The team is led by Dr. Tuomo Hartonen. We have active collaborations with leading researchers in the EU, UK and US, with opportunities for international research visits during the employment. We collaborate closely with several research groups at FIMM and at ELLIS Institute Finland. We work with diverse international datasets ranging from Finnish and French national health registries to biobank studies such as FinnGen (Finland), UK Biobank (UK) and All of Us (United States). Contract and salary The position is initially offered for two years, and can be possibly extended. A trial period of six months will be applied. The starting salary will be ca. 3900-4100 euros/month, depending on the appointees’ qualifications and experience, and is based on the University of Helsinki salary system. The University of Helsinki offers comprehensive services to its employees, including occupational health care, support in access to high quality sports facilities, and vast opportunities for professional development. Standard Finnish pension benefits are provided for university employees. Apply at latest by August 16th, 2026. The call may be extended until a hiring decision is made. How to apply: The application should include: A one-page letter stating the motivation for applying to this position. A maximum two-page CV. List of scientific publications. An official copy of the PhD degree certificate. Contact information of 2 references (name, relation to candidate, e-mail and telephone number) who have agreed to provide a written statement on behalf of the applicant. Note that the references will be contacted only at a later stage of the process. To apply, please submit the application through the University of Helsinki electronic recruitment system by clicking on Apply for job. Internal applicants (i.e., current employees of the University of Helsinki) please submit your applications through SAP Fiori https://msap.sap.helsinki.fi. For further information on the position, please contact Dr. Tuomo Hartonen (tuomo.hartonen@helsinki.fi).  A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions. Click this link to read about accessibility and inclusivity at our University. JOIN US TO BUILD A BETTER WORLD – TOGETHER! #HelsinkiUniCareers The Institute for Molecular Medicine Finland (FIMM) is an international research unit focusing on human genomics and personalized medicine at the Helsinki Institute of Life Science (HiLIFE) of the University of Helsinki - a leading Nordic university with a strong commitment to life science research. As part of Academic Medical Center Helsinki in Meilahti campus FIMM collaborates locally with the Faculty of Medicine, Helsinki University Hospital and National Institute for Health and Welfare. FIMM is part of the Nordic EMBL Partnership for Molecular Medicine, composed of the European Molecular Biology Laboratory (EMBL) and the centres for molecular medicine in Norway, Sweden and Denmark, and the EU-LIFE Community.

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the MCCS NATURE Project (https://www.nparks.gov.sg/Cuge/Programmes-Schemes/Research%20Programmes/MCCS%20Programme). The primary role involves developing and validating CFD models to study wave attenuation by mangroves, seagrass, and coral. Responsibilities include calibrating simulations with experimental data, analyzing shear coefficients and drag forces, and contributing to interdisciplinary research on coastal protection, with an emphasis on delivering accurate and impactful modeling insights. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: 1. Wave Stochastic Analysis and Hydrodynamics Conduct advanced stochastic analysis of wave environments to evaluate the performance of floating structures.  Analyze hydrodynamic behavior of floating breakwaters under varied sea conditions. 2. CFD and Finite Element Modeling Perform Computational Fluid Dynamics (CFD) simulations to optimize the design and performance of floating breakwaters. Develop finite element models for stability assessment, structural integrity, and dynamic response of floating systems. 3. Connector Design Design and analyze mechanical connectors for the integration of multi-purpose floating breakwater systems, ensuring structural stability and durability. 4. Design and Integration Develop innovative designs for floating breakwaters that integrate wave energy converters (WECs), tidal energy systems, and solar energy platforms. Optimize design configurations to maximize energy harnessing and wave attenuation. 5. Experimental Testing Plan and conduct physical model tests in wave flumes or basins to validate computational models. Analyze experimental data to improve and validate the floating breakwater design. 6. Research Documentation and Dissemination: Prepare technical reports, research papers, and presentations to disseminate findings to academic and industry stakeholders. Contribute to project proposals and progress updates for funding agencies. Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations. 7. Project Management Support: Ensure timely execution of project milestones Coordinate with external collaborators and manage data-sharing protocols. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements PhD/Master’s in Naval Architecture, Ocean Engineering, Civil Engineering, or related field. Proficiency in hydrodynamic modeling tools (e.g., ANSYS AQWA, OrcaFlex) and finite element analysis software (e.g., Abaqus, ANSYS). Experience with stability and mooring system design. Strong analytical skills and familiarity with data collection instruments and techniques. Excellent communication and report-writing abilities. Good understanding of industry standard will be an advantage Ability to work independently and in teams in both lab and field environments. Excellent communication (verbal and written) and teamwork abilities Key Competencies Able to build and maintain strong working relationships with people within and external to the university. Self-directed learner who believes in continuous learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work

Job Responsibilities Teach and assess at least 3 courses from the following 4 core subjects: Programming 1(Python) Fundamentals of AI Data Analytics & Machine Learning Deep Learning Develop course materials and curricula aligned with international standards and industry practices in AI, machine learning, and electrical engineering applications. Engage in applied research and publish in peer-reviewed journals. Collaborate with industry partners on AI-driven electrical systems, data analytics, predictive maintenance, and intelligent automation projects. Supervise student projects related to AI applications, machine learning models, data-driven engineering, and intelligent electrical systems.   Job Qualifications Master’s degree or above in Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, Data Science, Automation, or a closely related field. Strong background in artificial intelligence, machine learning, data analytics, and programming. Proficiency in Python and experience with AI/ML frameworks. Practical industry experience in AI, automation, smart systems, or electrical engineering applications is an advantage. Excellent communication skills and a strong commitment to high-quality teaching in an international environment. Proficiency in English; knowledge of German and/or Chinese is a plus but not required.   Expected Onboarding Date August 2026 Salary and Benefits Competitive Salary in the Market (13th Month Salary) Allowance: Travel Allowance / Phone Allowance / High Temperature Allowance, Etc. 5 Types of Social Insurance and 1 Housing Provident Fund Commercial insurance Transitional Apartments Arrangement Working environment that is open to the world and strongly oriented towards sustainability, diversity and internationality Paid Holidays Statutory Holidays (13days) Annual Leave (25 days) Paid Sick Leave Paid Marriage Leave Paid Maternity Leave Paid Paternity Leave Parental Leave How to apply Please prepare the following documents: Current English CV(including full publication list) Cover Letter(addressed to the President) 2 Reference Letters Teaching Qualification Documents, Qualifications (if available) Documents certifying the professor’s (if available) Academic Degree Certificates Please import all files into one PDF Please name the PDF as ” Position – Your Name” Please send all files to recruitment@hibiuh.edu.cn