About me
Computational biologist with a decade of experience (since graduate research in 2016) turning large-scale, multimodal, high-dimensional biological data into statistically validated, actionable results, most recently across single-cell multi-omics, immune repertoire, and proteomics datasets in a neuroimmunology research field. Proficient in Python, R and SQL, with deep hands-on experience in distributed/HPC servers, containerized pipelines, and machine-learning-based analysis. Alongside the analysis work, I’ve independently built and administered the Linux server infrastructure behind it, from HPC/Slurm setup to multi-user services and clinical data governance.
Skills
- Programming & data: Python, R, SQL, Git/GitHub, Bash
- Statistics & machine learning: hypothesis testing and statistical modeling, ML-based clustering and classification, trajectory/pseudotime (time-series-style) inference, network inference algorithms, simulation and quantitative modeling
- Multimodal data integration: combining heterogeneous, high-dimensional data streams (transcriptomic, epigenomic, proteomic, immune-receptor) into integrative analyses
- Systems & infrastructure: 10 years as a Linux user; independently set up and administered a dedicated group server (full OS-admin rights): Slurm scheduling, conda/container environment management (Docker/Singularity), multi-user services (RStudio Server, Jupyter Notebook), and data storage/backup policy, including encryption and governance for clinical data
- Reporting & tools: HTML/CSS, Shiny applications for interactive data reporting
Education
- PhD in Biotechnology (2018-2023) | Gebze Technical University - Kocaeli, Turkey
- MSc in Molecular Biology and Genetics (2016-2018) | Gebze Technical University - Kocaeli, Turkey
- BSc in Biology (2012-2016) | Marmara University - Istanbul, Turkey
Research Experience
- Postdoctoral Researcher (2025-Present) | University of Helsinki - Helsinki, Finland
- Built statistical and machine-learning pipelines to profile immune cell populations from multimodal single-cell data, tracking how disease-modifying therapies shift cellular-level readouts over time in MS patients.
- Own data management strategy for sensitive clinical research data (encryption, storage policy) and manage HPC project resources: user and data allocation, pipeline development, and containerization.
- Postdoctoral Researcher (2023-2025) | Karolinska Institutet - Stockholm, Sweden
- Modeled cell-cell interaction signals from multi-omic data to characterize brain-vascular changes in ALS and MS, integrating results across species for comparative analysis.
- Set up and administered the group’s dedicated Linux server end-to-end (full OS-admin rights): configured Slurm job scheduling, deployed and maintained multi-user RStudio Server and Jupyter Notebook environments, and owned data storage and backup strategy.
- Guest Researcher (2021-2022) | Max Planck Institute of Biological Intelligence - Munich, Germany
- Ran trajectory and network-inference analyses on multimodal single-cell data (transcriptomic + epigenomic) to model neuron development, including motif enrichment and gene-oscillatory-network analysis.
- Developed a Python tool implementing a lineage-tracing algorithm for single-cell DNA barcoding data.
- Maintained Linux workstations and HPC cluster infrastructure for the group: built reproducible conda environments and Docker/Singularity containers for other researchers’ analysis workflows, with ongoing R/CLI tool maintenance.
- Research Assistant (2019-2023) | Gebze Technical University - Kocaeli, Turkey
- Performed transcriptomic and genomic analyses of nervous system development and gene regulation, including gene regulatory network inference.
- Built quantitative kinetic models of transcription-factor regulation, and ran cell-culture-based validation experiments.
- Maintained the department’s website (announcements, exam results) as governmental university staff, hand-coding HTML/CSS where the built-in CMS fell short.