The topics I work on are diverse (biology, ecology, finance privately) but they share one common goal: interpret data to understand processes. I often contribute to specific tasks within a project and sometimes I manage the entire process from data to insights (i.e., scientific publication). In all cases, I focus on providing a concise solution specifically tailored to the project and your needs. This may include experimental design, data analytics, scientific writing, and preparing a data management plan for SNSF grants. In addition, I also offer customized training and teaching.
The success of a scientific project critically depends on the design of the experiments. Often, this requires a good understanding of the technology employed and experience with the analysis of the data produced by it. I can directly design experiments involving omics (e.g., RNA-Seq, BS-Seq, and ChIP-Seq) and I maintain active contacts with academic experts for more general experimental designs (e.g., ecological field experiments).
Data analytics are the core of my work as a scientist. I employ techniques from classical statistics, mathematical modelling, and machine learning to turn data into insights. I use widely adopted open-source software packages for the implementation of my analytics (mostly R and sometimes Python). Whenever needed, I develop new packages (R), implement novel algorithms (R, Python, C++), or write workflows for distributed computing on cloud infrastructures. To ensure reproducibility, I keep track of my analytics by documenting each and every step. My core expertise are omics data (e.g., RNA-Seq, BS-Seq, ChIP-Seq, 16SRNA-Seq, 4C, HiC, reduced representation sequencing) and ecological data from field experiments. However, I am genuinely interested in any type of data.
Data analytics are tightly connected to scientific communication: manuscript and project proposal writing, internal reporting, and content for conference presentation. I have so far managed several entire projects from data to the final publication (Research). This included data analysis, interpretation, visualization, and writing the manuscript. Based on this experience, I offer support in scientific writing and I deliver publication ready content derived from my data analytics.
Data Management Plan for SNSF Grants
From October 2017 on, the Swiss National Science Foundation (SNSF) requires researchers to include a data management plan (DMP) in their funding application (Open Research Data). The SNSF also expects that data generated by funded projects will be publicly accessible in digital databases. Working together with different research groups, I know which kind of documentation and metadata are required to understand and effectively share data. However, I am also aware that certain data management policies can inhibit creativity and innovation. Aside discussing or writing your DMP, I also offer to implement it during the course of your SNSF funded project.
Training and Teaching
Many fields in life-sciences experienced a rapid digitalization. This requires a realistic, flexible, and swift adaptation of analytical skills. For example, molecular biologists should not aim to become experts in biostatistics and bioinformatics within a short 1-2 years time-line, in parallel to their daily research and experimental workload. Instead, with a carefully focused and tailored training and education, experts in biology can acquire thorough basic skills that allow them to independently and correctly perform analytics at their level. Furthermore, such skills promote efficient communication with bioinformaticians, converging in an overall better analytics that benefits from collaborative work of mixed expertise. I offer one-on-one or small group teaching and hands-on training in specific aspects of programming and data analytics. In addition, I maintain good contacts with academic and non-academic experts for programming, data analytics, and statistics to whom I can forward requests I cannot cover myself.Go to top