Research Prime

PostDoc Machine Learning Methods for Quantum Chemistry (m/f/d)

Organisation Name: Bayer Inc.
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Job Description:

 

At Bayer we’re visionaries driven to solve the world’s toughest challenges and striving for a world where Health for all Hunger for none’ is no longer a dream but a real possibility. We’re doing it with energy curiosity and sheer dedication always learning from unique perspectives of those around us expanding our thinking growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference there’s only one choice.

 

PostDoc Machine Learning Methods for Quantum Chemistry (m/f/d) 

 

The Applied Mathematics group within Bayer is looking for a scientist with expertise in machine learning and chemistry to join Bayer Engineering & Technology in Leverkusen Germany. The successful applicant will be part of an interdisciplinary and cross-divisional team within the R&D organization and will contribute to the implementation of novel machine learning methods and predictive models for chemical property prediction. In detail: 

 

YOUR TASKS AND RESPONSIBILITIES

  • To increase the efficiency of our R&D functions you develop application driven machine learning models for molecular property prediction
  • You work on the interface of quantum chemistry and machine learning and develop models that bridge both worlds
  • You design compose and deliver presentations and publications
  • You collaborate and interact with an international interdisciplinary cross-divisional team comprising of theoretical chemists mathematicians machine learning experts and experimental chemists

 

WHO YOU ARE

  • PhD in natural science or computer science with strong background in machine learning/data driven modeling
  • Profound knowledge in computational chemistry (preferred quantum chemistry)
  • You have extensive experience in developing and applying machine learning approaches in the context of chemistry (e.g. molecular spectra 3D descriptors modeling of wavefunctions)
  • You are familiar with state-of-the-art machine learning methods model selection and deep learning concepts and have a strong willingness to further develop expertise in these areas (preferred knowledge in Pytorch and/or Tensorflow)
  • Profound knowledge of Python
  • You are able to handle the necessary data engineering tasks especially in the context of chemistry
  • Willingness and curiosity to learn experimental set-ups novel mathematical approaches as well as to dig into Pharma- and Crop Science-R&D
  • You are able to work in interdisciplinary teams with excellent interpersonal and communication skills
  • High level of English communication skills in verbal and written form 

 

Funding of this position is made available through the Bayer Life Science Collaboration program. The goal of this program is to promote state-of-the-art research within Bayer´s R&D organization especially focusing on cross-divisional exchange and impact.

 

The position is limited for 2 years. 

 

YOUR APPLICATION

This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health feeding growing populations and slowing the rate of climate change. You have a voice ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer.

Bayer welcomes applications from all individuals regardless of race national origin gender age physical characteristics social origin disability union membership religion family status pregnancy sexual orientation gender identity gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.
 

Location:               Leverkusen

Division:                Enabling Functions

Reference Code:  460781

 


Posting Date: Nov 27, 2021
Closing Date:
Organisation Website/Careers Page: https://career012.successfactors.eu/career?company=C0003153479P&career_job_req_id=460781&career_ns=job_application&src=Eightfold


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