At: Hellas Foundation for Research and Technology
Location: Heraklion, Crete, Greece
The Bioinformatics Laboratory (BIL) is a recent laboratory of the Institute of Computer Science at the Foundation for Research and Technology, Hellas (FORTH), founded in 2011. BIL is also affiliated with the Computer Science Department of the University of Crete. BIL has recently secured funding in competitive and exciting EU research grants and is looking to expand by hiring ambitious, energetic, intelligent, and hard-working individuals to lead the development of novel causal discovery and machine learning methods, particularly for bioinformatics and computational biology problems. BIL members have pioneered state-of-the-art methods for variable selection, for learning causal models, and most recently for Integrative Causal Analysis, a new approach to learning from multiple and heterogeneous datasets. Overall, FORTH is ranked first among Greek research institutions in number of citations and 12th among European research institutions in EU FP7 funded-project participations.
A Ph.D. degree is required in the fields of machine learning, data mining, statistics, biostatistics, applied mathematics, operations research, or related fields. A proven research record in one of the above fields is a prerequisite.
Responsibilities include the development of computer code, the analysis of biological data, the development of novel algorithms, participating or leading the writing of project deliverables and scientific papers. Active participation in proposal writing and management is also required. In addition, participation in the laboratory's educational activities is also desired (e.g., supervising M.Sc. students, presenting tutorials, etc.).
Knowledge and skills in any of the fields below is highly valued during applications' consideration:
- Computational Causal Discovery methods (e.g., Causal Bayesian Networks, Maximal Ancestral Graphs, Structural Equation Models, etc.)
- Relational learning methods
- Time-series analysis, particularly with Causal-based methods
- Method for learning systems of Ordinary differential equations
Dateline: Apply until November 1st, 2012.
Head of Bioinformatics Laboratory
Institute of Computer Science, Foundation for Research and Technology, Hellas
email: email@example.com Tel: +30 2810 391617