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relevant programming languages (Python, Perl, R). A good understanding of molecular biology, genomics experiments and bioinformatics is expected. Candidates with proven track record in terms of publications
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Recruitment Type Open Position Details General Statement PhD in a relevant field, experience with data science, remote sensing, modeling, and strong capabilities in R and/or Python are required. Additionally
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languages (e.g. Python) would be an asset. You should also have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and as part of a team
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include algorithm design, prototype implementation (e.g., in Matlab/Python), deployment (to the agents’ autopilots using the Robot Operating System), and experimental testing (on unmanned vehicle swarms). A
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the core Python application, ii) major contributor to the project ecosystem design and implementation, iii) coordinator of working groups, and iv) major contributor to project presentations and publications
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Bioinformatics and/or Cheminformatics. Experience working in computational drug discovery, particularly multiscale applications. Experience working in Python and Bash. Understanding of machine/deep learning topics
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) or reactive transport simulation codes (e.g., OpenFOAM, StarCCM+, PFlotran, TOUGHREACT, PHT3D etc.). Good programming skills in C/C++, Fortran, or Python. Knowledge and experience with HPCs. The work will be
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with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets Demonstrated research competence and initiative through inernational publications in peer-reviewed
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models using software such as GAMS and Python. Econometric modeling skills using statistical software (e.g., Limdep, Stata, EViews or R). Strong programming skills with R and Python. Excellent oral and
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with