Undergraduate or graduate students
Students who are considering Bachelor's or Master's thesis projects are welcome to contact Dr. Xin Lai and share their areas of interest. We offer several topics, including data analysis, mathematical modeling, and machine learning. All require programming skills, such as R, Python, or MATLAB. If you are a medical student, we could offer a topic on meta-analysis, which does not require programming skills. Here is an exemplar thesis that was conducted in the laboratory.
Ph.D. students
For students aspiring to pursue Ph.D., we kindly request that you include your résumé, academic transcripts, an accepted English proficiency test (such as TOFEL and IELTS; if you are from outside of EU or a non-English speaking country), and a letter of intent when sending your email to Dr. Xin Lai. Additionally, attaching an one-page research proposal and articulating why you've chosen our lab can significantly enhance your application.
Our faculty has a regular call (usually in February) for doctoral researchers and the funding can support your Ph.D. study up to 4 years. If you are interested, please contact Dr. Xin Lai 3 months in advance to prepare for the application because you need to submit a research proposal for the application.
Postdocs
If your research objectives align with our laboratory's focus, we are more than willing to provide support for your application, particularly if you are seeking external funding opportunities. Please contact Dr. Xin Lai 4 months in advance to prepare for the following applications.
We can help you apply for open positions at the Tampere Institute for Advanced Study (February-March every year).
We also offer university-level support (5 training courses) to help you prepare and apply for the prestigious MSAC Postdoctoral Fellowship (April-September each year).
Interested applicants should contact Dr. Xin Lai by providing a résumé including 2-3 references. Specifically, we expect the applicant to have
strong coding skills: (R | Python | MATLAB);
strong computational and quantitative background (e.g., statistics, computer science, mathematics, physics, bioinformatics, and computational biology) or substantial experience in healthy or molecular data science (e.g., omics data analysis, bioinformatics applications, etc.);
first-author publication(s) in your own field, with accepted or published status in journals or conference proceedings;
strong oral and written communication skills in English.