PhD scholarship in machine learning for enzymology at DTU Biosustain

Employer
DTU Biosustain
Location
Copenhagen, Hovedstaden (DK)
Salary
-
Closing date
Feb 13, 2023

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Field of specialization
Biochemical, Biological, Engineering
Work Function
Research-Applied
Job Type
Temporary
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PhD scholarship in machine learning for enzymology

Are you establishing your career as a scientist and looking for the best possible foundation for fulfilling your ambitions? At the Enzyme Engineering and Structural Biology (EE&SB) research group of DTU Biosustain you will have the opportunity to contribute to the growing interdisciplinary field of machine learning in enzymology. We are probing what’s possible by combining machine-learning methods with custom experimental datasets generated in house to explore the enzymatic space for sustainable industrial applications.

 

If you are interested in using enzymes to increase our society’s sustainability, perhaps you are our new PhD student. As a PhD student in EE&SB you will

  • Have the opportunity to define your project within our frame to fit your own research interests Teach and supervise younger students Go to international conferences to promote your work Be an active member of EE&SB and contribute to many ongoing projects Develop intellectual property and business cases

Responsibilities and qualifications
Your PhD project will focus on developing methods to predict and design the reactivity, substrate scope, and stability of enzymes of the glycosyltransferase type. You will be responsible for driving and disseminating your own research within this frame, as well as for supervising junior students.

 

We are looking for a candidate who are highly motivated, self-driven and have demonstrated excellence in their previous work.

 

Responsibilities:

  • Lead your research guided by your supervisors Disseminate your research results in academic publications, scientific conferences, and patents as relevant. Supervise junior students Be an active and collaborative member of our research group Develop algorithms for predicting and designing enzymatic properties Optionally, generate laboratory data to train and validate your algorithms

Qualifications:

  • Scientific curiosity and ambition Coding skills Preferably experience in machine learning (for biology), or other in silico biology methods Laboratory experience is an advantage English skills in speech and writing are an advantage

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

 

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

 

Assessment
Candidates with experience in machine learning, enzymology, and scientific publishing or patents will be given priority. The assessment will be made by main supervisor Ditte Hededam Welner (group leader of EE&SB), co-supervisor Stanislav Mazurenko (leader of AI in Protein engineering team, Loschmidt Laboratories), and members of EE&SB.

 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

 

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

The preferred starting date is 1 May 2023, or according to our mutual agreements. The position is full time.

 

You can read more about career paths at DTU here.

 

Further information
Further information may be obtained from Ditte Hededam Welner, diwel@biosustain.dtu.dk, +4593513498

 

You can read more about

 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

 

Application procedure
Your complete online application must be submitted no later than 13 February 2023 (Danish time).

 

Apply at: PhD scholarship in machine learning for enzymology

 

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

 

  • A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

 

Applications received after the deadline will not be considered.

 

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

 

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

 

 

 

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