Computational Scientist
Hartmann Young
Baden-Württemberg, Germany, Germany
As a Computational Scientist , you will be pivotal in designing and implementing advanced simulation and machine learning algorithms to support our digital twins technology.
Your work will focus on performance optimisation of our core algorithms, development of prototypic code, and rigorous testing and debugging to ensure the highest levels of reliability and efficiency within our development cycle.
You will also contribute to the advancement of statistical methods and machine learning techniques, playing a key role in maintaining our position as a leader in biopharmaceutical innovation.
Key Responsibilities
- Design and implement cutting-edge simulation algorithms to model complex bioprocesses.
- Develop and optimise machine learning algorithms to enhance predictive accuracy and efficiency.
- Perform performance optimisation for all our core algorithms, ensuring scalability and high efficiency.
- Develop prototypic code for new algorithms, facilitating rapid testing and iteration.
- Conduct comprehensive testing of our algorithms to ensure robustness and reliability.
- Advance statistical methods and machine learning techniques applicable to bioprocess modelling and optimisation.
- Enhance our machine learning algorithms to ensure a high predictive quality.
Key Skills and Qualifications
- Strong foundation in algorithms and data structures, with proven expertise in developing high-performance computational solutions.
- Proficient in scientific programming with Python, C++, and Java.
- Experience with machine learning frameworks (e.g., TensorFlow, JAX, PyTorch).
- Experience with mathematical optimization solvers (e.g. CPLEX, Gurobi, SNOPT, Ipopt, Knitro)
- Knowledge of optimization algorithms, stochastic methods, and Karush-Kuhn-Tucker conditions.
- Familiarity with numerical solvers for ordinary and partial differential equations.
- Understanding of probabilistic programming, and comprehensive knowledge in statistics and stochastics (both frequentist and Bayesian approaches).
- A degree in Computer Science, Computational Biology, Bioinformatics, Mathematics, or a related field. Advanced degrees (MSc or PhD) preferred.
- Excellent problem-solving abilities, attention to detail, and a commitment to scientific excellence.
Vor 23 Tagen