PostDoc position in Computational Chemistry

Apply now to join Boehringer Ingelheim as part of the prestigious PostDoc grant program opn2TALENTS and have the chance to pursue your own submitted research project as a fully resourced two-years PostDoc (with the option for a one-year extension), in the Computational Chemistry group at Boehringer Ingelheim, Biberach, Germany.

For this PostDoc grant via opnMe, we invite you to submit your research plan that focuses on the development and combination of 3D-generative models and potency predictions for drug design. A successful research proposal to our question will focus on these topics:

  1. How to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches?
  2. How would you integrate machine learning, physics-based methods in an early-stage of a project with limited experimental data points?
  3. In addition, how would you combine various computational chemistry methods that can leverage data to enhance potency predictions?

With your solution, you will be able to benefit from the ecosystem of a large pharmaceutical player and at the same time contribute to better drug design with improved predictive models. 

What potential solutions could be in scope?

  • Critically assessing the added value of 3D-based generative modelling compared to 2D-based approaches
  • Tailored reward functions towards specific design objectives
  • Dynamically incorporating new in-house data, thereby continuously improving predictive accuracy
  • Establishing potency models using a range of different Computational Chemistry methods

What potential solutions would be out of scope?

  • Generative molecular design solely focused on the 2D world
  • Proposals that would take more than 2 years to complete

What are the requirements to participate in this call?

Your proposal outlining your own research plan should contain a clear description of the planned combination of computational chemistry methods focused on 3D-based generative modelling, and a strategy of training potency models with fewer data points and tailored reward functions towards design objectives while generating molecules in 3D.

Additional requirements:

  • Doctoral degree (PhD) in computational (medicinal) chemistry, computer-aided drug design or a related field. Track record of scientific innovation, as demonstrated by scientific publications, patents, relevant presentations, or software code.
  • Demonstrated experience in structure- and ligand-based drug design methods (e.g., docking, QSAR, classic molecular dynamics, etc.)
  • Familiar with all aspects of protein-ligand interactions.
  • Solid python programming knowledge and good code quality is a must.
  • Additional knowledge on machine learning (e.g., scikit-learn, Pytorch, and generative chemistry) and free energy calculations is beneficial.
  • Outstanding creativity, critical thinking, and analytical as well as problem-solving skills.
  • Enthusiastic, self-motivated, and result-driven with a strong desire to achieve scientific excellence and the will to challenge the status quo.
  • Strong communication and presentation skills, capable of conveying project information in a clear manner to discipline experts

What information should be included in your answer submission?

Please use our PostDoc grant application template to provide a 4–5-page non-confidential proposal. Please complement with your CV, publication list, and recommendation letters.

If confidential data exists that would strengthen the proposal, please indicate that information is available to share under a Confidential Disclosure Agreement (CDA). If we find the non-confidential concept proposal sufficiently interesting, we will execute a CDA for confidential discussions.

 What will be the reward to the winner?

As a winner of this call, you will have the unique opportunity to pursue your own submitted research project as a fully resourced two-years PostDoc (with the option for a one-year extension), in the Computational Chemistry group at Boehringer Ingelheim, Biberach, Germany.

As part of an international team of world-class scientists working on computational drug design you will learn the processes and challenges of drug discovery in the pharmaceutical industry from the inside.

 At Boehringer Ingelheim, you will have access to a fully equipped state-of-the-art research facility including access to all relevant tools and HPC-enabled technologies. You will benefit from mentoring through our internal experts, have the chance to attend international conferences, and publish your results in high-ranking journals. You will be part of the vibrant PostDoc and data science and AI community at Boehringer Ingelheim in Biberach.

Working at Boehringer Ingelheim

  • Our purpose is to transform lives for generations. Therefore, we developed three key principles for our PostDoc program which are determining our plans and actions: Drive cutting-edge science, new concepts and technologies; enrich Boehringer Ingelheim’s innovation ecosystem with highly motivated, young fellows, who will help to build on science to develop new medicines; and train the next generation of leading scientists.
  • Our campus community culture is great for sharing ideas and makes it easy to access technologies, meet experts, and approach leaders of all levels. There’s a great spirit of freedom, fluidity, and fierce collaboration.
  • Interactions are sound and informal. It’s not particularly hierarchical, more team-based with a start-up attitude. We are always keen to help and speak up, open to positive change and new ideas that support our mission to improve lives.
  • Our Speak-Up policy is an important part of our Code of Conduct. Only in this way we can continuously develop and improve as a company.
  • Diversity, Equity, and Inclusion (DEI) is an integral part of Boehringer Ingelheim’s identity; a key element of our culture and contributes to our ‘Sustainable Development – For Generations’.
  • Our core values of empathy, respect, passion, and trust nurture a diverse, collaborative, open and inclusive environment which is key to innovation, value creation and sustainable growth. With the inclusion of various experiences, backgrounds, and characteristics, Boehringer Ingelheim creates an openness to different approaches, solutions, and perspectives, all contributing to create “Value through Innovation”.


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Source: https://www.nature.com/naturecareers/job/12838337/postdoc-position-in-computational-chemistry/?LinkSource=PremiumListing

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