We are looking for highly qualified and motivated Doctoral Researcher to join, Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE) at The Faculty of Medicine and Health Technology (MET) at Tampere University. We are seeking a highly motivated PhD student to join our research team. The student will focus on developing innovative computational methods, tools, and APIs in R (and Python) to support projects in toxicology, drug discovery, and sustainable material design. While prior biology knowledge is not required, the candidate should have a strong interest in learning and collaborating within interdisciplinary research teams. In this position, you will have an opportunity to work on cutting-edge interdisciplinary research projects with real-world applications in toxicology, drug discovery, and sustainability (such as INSIGHT, PINK, and CHIASMA).
As a doctoral researcher your work will include:
- Designing and developing computational tools, workflows, and APIs in R and Python
- Development of data curation and exploration analytical pipelines for large-scale datasets
- Contributing to the development of graphical interfaces to enhance the usability of computational tools and APIs.
- Collaborate with biologists, chemists, and toxicologists to understand project needs and tailor computational solutions.
- Document and share code using best practices (e.g., git).
Requirements
You need to have an applicable master’s degree in computer science, data science, computer engineering, bioinformatics, chemical engineering, or a related quantitative field. The position requires:
- Programming Proficiency:
- Experience in R and python programming, including data science and Machine Learning packages
- Experience in R and python packages development and APIs and scripting. (e.g., using Plumber, RStudio Connect, or Shiny, fastAPI, flusk, openAPI),
- Statistical Knowledge: Proficiency in applying and implementing statistical methods
- Problem-Solving Skills: Ability to translate complex research questions into computational solutions
- Data Handling: Experience working with large datasets, including cleaning, wrangling, and integration.
- Communication Skills: Ability to present computational results to non-technical collaborators.
- Willingness to Learn Biology: Interest in toxicology, pharmacology, or related fields to contextualize computational tools.
- Independent and team work
Desired Skills (Not Required, but a Plus)
- Knowledge of biological or toxicological data and relevant analysis techniques (RNASeq preprocessing or analysis, QSAR, dose-dependent analysis)
- Hands-on experience with containerization tools like Docker
- Experience with Snakemake for pipeline development
- Experience with network analysis (e.g. networkX, igraph) and knowledge graphs (Neo4j)
More information about the position can be found here.
Application are open and can be submitted here by March 28th, 2025 at 23.59 (EET).
For further information, please contact:
Professor Dario Greco, dario.greco@tuni.fi
University Lecturer Angela Serra, angela.serra@tuni.fi
Postdoctoral Research Fellow Michele Fratello, michele.fratello@tuni.fi