查尔姆斯理工大学

AI guided design for next generation peptide drugs

项目介绍

Would you like to be part of an enthusiastic collaborative cross-disciplinary team that is developing the peptide drugs of the future?

We’re currently looking for an industrial PhD student to join a collaboration between AstraZeneca and Chalmers University of Technology to develop a next generation peptide drug discovery platform with a focus on creating a machine learning based pipeline to design and predict novel peptide drugs with improved properties. The innovative project is embedded in an ongoing interdisciplinary collaboration project for peptide based drug discovery between Chalmers University and AstraZeneca.

What’s more, you’ll have the support of leading scientists from Chalmers and AstraZeneca, who will provide you with the guidance and knowledge you need to advance in your PhD project. You will be part of the Bioscience Graduate School at Chalmers University of Technology and be a member of the vibrant Molecular AI team at AstraZeneca developing novel ML/AI methods for peptide drug design. The successful candidate will be an employee of AstraZeneca for the duration of the PhD studies.

Working in the intersection of academic research and industrial driven applications is an opportunity to make a real difference to the future of medical science.

About the Division of Systems and Synthetic Biology 
The Division of Systems and Synthetic Biology (Sysbio) at Chalmers University is a diverse group of scientists working on systems biology questions that influences the progress of biotechnology and the understanding of human diseases. The SYSBIO team has over 80 members, with about half of the scientists working at the bench, and half working with computational modelling.

The details of the departmental research activities may be found here.

About the Molecular AI team at AstraZeneca
The Molecular AI team impacts drug discovery projects through applying machine learning and AI to drug design. The team drives the science forward through developing novel deep learning methods to generate novel molecules, predict synthetic routes and molecular properties. The team has built two platforms for molecular de novo design and synthesis prediction, respectively. The team consists of approximately 20 members including staff scientists, postdocs, PhD students and graduate students. 

Major responsibilities
The open PhD position is in the field of applying machine learning to peptide drug discovery. You will be able to work seamlessly between two world leading institutions at Chalmers University and AstraZeneca, co-located in Gothenburg to bring your PhD project into reality.
Your project will include the curation and analysis of peptide data sets, data mining, building of machine learning models for property predictions and extend the current deep learning based small molecular generation methodology to peptides. You will have access to state-of-the-art computational clusters for building the machine learning models and for in silico generation of novel structures. The successful candidate will have the opportunity to supervise MSc students.

You have developed excellent bioinformatic or machine learning skills and now wish to apply them in a new way. You will be a creative problem solver, who sees challenge problems as opportunities to innovate. You will have a passion for teamwork and recognize the value of a strong network and working in an international multidisciplinary environment.

Positions summary
Full-time employment for 4 years + additional 10% for teaching at Chalmers University. Employer: AstraZeneca. 

Qualifications
Master of Science or equivalent in a relevant subject for instance bioinformatics, engineering mathematics or complex adaptive systems. The candidate should have taken advanced courses in machine learning and preferably taken courses in computational biology/chemistry as well as basic chemistry/biology.

The position requires sound verbal and written communication skills in English. 

Application procedure
The application should be marked with Ref 20210204 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities)
• Describe your future goals and future research focus

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.

Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).

Application deadline: 23 May 2021

For questions, please contact:
– Florian David, Assistant Professor, Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, davidfl@chalmers.se
– Ola Engkvist, Head Molecular AI, AstraZeneca, Gothenburg, ola.engkvist@astrazeneca.com
– Andy Davis, Senior Principle Scientist, AstraZeneca, Cambridge, Andy.Davis@astrazeneca.com

项目职责

  • The open PhD position is in the field of applying machine learning to peptide drug discovery. You will be able to work seamlessly between two world leading institutions at Chalmers University and AstraZeneca, co-located in Gothenburg to bring your PhD project into reality.
  • Your project will include the curation and analysis of peptide data sets, data mining, building of machine learning models for property predictions and extend the current deep learning based small molecular generation methodology to peptides. You will have access to state-of-the-art computational clusters for building the machine learning models and for in silico generation of novel structures. The successful candidate will have the opportunity to supervise MSc students.
  • You have developed excellent bioinformatic or machine learning skills and now wish to apply them in a new way. You will be a creative problem solver, who sees challenge problems as opportunities to innovate. You will have a passion for teamwork and recognize the value of a strong network and working in an international multidisciplinary environment.

录取要求

  • Master of Science or equivalent in a relevant subject for instance bioinformatics, engineering mathematics or complex adaptive systems.
  • The candidate should have taken advanced courses in machine learning and preferably taken courses in computational biology/chemistry as well as basic chemistry/biology.
  • The position requires sound verbal and written communication skills in English.

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截止日期 2021-05-23
查尔姆斯理工大学

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查尔姆斯理工大学是一所以工程技术、自然科学和建筑学的教育与研究为主旨的欧洲顶尖理工院校。
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