You: We are looking for talented, intelligent, hard-working, independent-thinking researchers, Ph.D. or M.Sc. students, and scientific developers. Leadership skills, taking the initiative, independence in research, good communication, and English writing skills are greatly appreciated.
We: The MensXMachina is an internationally known academic group in the Computer Science Department of the University of Crete, also affiliated with the Institute of Applied and Computational Mathematics of the Foundation for Research and Technology, Hellas. Our group includes several talented, young researchers and students, as well as faculty (Profs. Tsamardinos, Triantafillou, Christophides). We do research in the core of machine learning algorithms, bioinformatics, and artificial intelligence, as well as numerous interdisciplinary applications with a focus on biomedical applications of machine learning. In machine learning, we focus on feature selection, causal discovery, and automated machine learning. Our published research receives more than a thousand citations per year. We have an entrepreneurial mentality having founded the JADBio (jadbio.com) start-up and University spin-off, and close collaboration with the industry as our funding includes industrial projects.
Why: We have just been awarded an ERC Proof-of-Concept grant to create the first automated causal discovery tool, a bioinformatics-related grant from the Norwegian University of Science and Technology to perform pioneering lung-cancer research, and an industrial grant from the industry on causal analysis of cellphone data. Our group regularly participates in numerous grant applications and more grants are expected soon.
- Contractual Researcher (Ph.D. level) in machine learning, causal discovery, and modeling: The project regards research on causal discovery and modeling from spatiotemporal data. Research on designing novel algorithms and/or optimal modeling of data. A Ph.D. in statistics, machine learning, or related field is required. Solid knowledge of statistical theory and methods. Previous experience with causal inference or probabilistic graphical models is desirable, but not required.
- Scientific developer (M.Sc. level or higher) for causal discovery and modeling: The project regards research on causal discovery and modeling from spatiotemporal data. Implementation of algorithms, analysis pipelines, and extensive analysis experiments.
- Scientific developer (M.Sc. level or higher) for data cleaning and feature construction algorithms.
- Contractual Researcher (Ph.D. level) in bioinformatics. The project regards the analysis and modeling of lung cancer multi-omics datasets and the design of novel bioinformatics and machine learning algorithms. Experience with transcriptomics, proteomics, metabolomics, and genetic data are appreciated. A solid statistics background is appreciated.
- M.Sc. students who’d like to do research and a master’s thesis in the fields of causal discovery and machine learning.
When: Rolling deadline until positions are filled.
Where: Ideally, the applicants will be hosted in the Computer Science Department of the University of Crete (www.csd.uoc.gr) or the Institute of Applied and Computational Mathematics, FORTH (www.iacm.forth.gr), in Heraklion, Greece, but they may also work from a distance.
How: Please send an updated CV to all three email addresses: Ioannis Tsamardinos firstname.lastname@example.org, Glykeria Fragkioudaki email@example.com, and Sofia Triantafillou firstname.lastname@example.org, with the subject “[Application Position n]”, where n is the number of the position you are applying for. Short-listed applicants will be interviewed. The email is meant to express interest; a formal hiring procedure will be commenced for successful individuals by the academic institution.
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