JOBS

We acknowledge Vitalina Kirgizova forthe provided picture with a snowman.
We are constantly looking for new professionals on constant or part-time basis in the next fields:
  • Chemoinformatics, QSAR, structure-based drug design and ligand-based drug design, molecular modeling
  • Programming (R, Python, Java, PhP, C/C++, Perl etc.)
  • Mathematics and IT (statistical analysis, machine learning and deep learning algorithms, artificial intelligence)
  • Organic synthesis
  • Medicinal chemistry
  • Molecular and cellular biology
  • Bioinformatics
  • Structural biology
  • Robotics and experiments automatization
  • ADME/Tox, pharmacokinetics, toxicology
  • If you are ready to get paid in cryptocurrencies, please mention this in your application.
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News & Publications
Multi-omics approaches to disease
September 16, 2017 – 17:28
High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.

Entering the ‘big data’ era in medicinal chemistry
May 15, 2017 – 15:09
Medicinal chemistry is experiencing the advent of the big data era, which biology already entered more than a decade ago, due to the availability of high-throughput genomics technologies. In medicinal chemistry, which is an integral part of drug discovery and traditionally a conservative scientific discipline, big data primarily comprise rapidly increasing numbers of compounds and volumes of associated activity data.
While the practice of medicinal chemistry is just beginning to experience big data phenomena, it is evident that big data will play an increasingly important role going forward. More awareness of big data issues and potential caveats will still need to be raised to positively impact the field.



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