PhD Student Position in Generative models for Molecular Simulations

Chalmers Tekniska Högskola AB / Högskolejobb / Göteborg
2023-04-25
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Description
Molecular simulations allow researchers to study molecular processes in unprecedented detail. Molecular dynamics simulations have many uses, including drug discovery, materials science, and chemical reaction modeling. They can also be used to simulate biological systems such as proteins and nucleic acids. However, these simulations are computationally expensive, which limits their practical scope dramatically. In this project, the selected candidate will leverage generative AI to speed up simulations, to unlock the mechanisms of large molecular systems such as proteins.

Machine learning provides new exciting new opportunities in the natural sciences such as physics, chemistry, and biology. Its potential application areas span from designing new drugs against multi-resistant pathogens and understanding the impact of gene defects on a protein's function to speeding up computer simulations to understand fundamental scientific phenomena and design optimal algorithms for near-term quantum computers. The path toward these applications can leverage the power of deep learning to represent and process high-dimensional data effectively and encode natural laws and symmetries.

To join our group, we seek a collaborative and self-driven candidate with experience in statistical mechanics, machine learning, or dynamical systems, preferably a combination, either via coursework or through completed projects (e.g., publications or software libraries).

The Artificial Intelligence and Machine Learning for the Natural Sciences (AIMLeNS) group (head: Simon Olsson) is an interdisciplinary team of about ten researchers focusing on developing AI and ML systems to address outstanding challenges in the natural sciences. The recruited Ph.D. student will integrate into the AIMLeNS group. You can read more about the group at https://www.cse.chalmers.se/~simonols/

The selected Ph.D. student will lead the development of generative AI systems to speed up molecular simulations. The aim is to develop a system that enables large-scale protein simulation on long-time scales, with possible applications in molecular design and structural biology. The selected candidate will build upon the group's recent work and enjoy the group's open and collaborative environment (1,2).

1) Noe, Olsson, Kohler, Wu (2019) Science 365 (6457), eaaw1147
2) Viguera Diez, Romeo Atance, Engkvist, Mercado, Olsson. ELLIS Workshop ML4Mol (2021)

Information about the project
The project takes place at the Chalmers University of Technology, department of Computer Science and Engineering. The student will pursue a Ph.D. in machine learning in computer science and engineering at Chalmers and enroll in the WASP graduate school. The WASP program generously funds the research project. Below are brief descriptions of WASP and the WASP graduate school and links for more details.

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden's largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.
The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry.
Read more: https://wasp-sweden.org/

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry.
Read more: https://wasp-sweden.org/graduate-school/

Major responsibilities
As a Ph.D. student, you will enroll in a graduate program at the Department of Computer Science and Engineering, where your primary responsibility is to pursue your doctoral studies, which entails:
* 80% Research and course work
* 20% Service, including teaching

The research entails developing and implementing your scientific ideas, communicating your results orally or in written form. Service entails being a teaching assistant in Chalmers' undergraduate and masters-level courses or performing other departmental tasks.

Qualifications
To qualify as a PhD student, you must have a master's-level degree, or a four-year bachelor's degree, corresponding to at least 240 higher education credits in a relevant field. The degree should have been awarded at the latest at the time of start of the position. The position requires sound verbal and written communication skills in English. If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure
Follow link to Chalmers webpage where you find the add and details on application procedure: PhD Student Position in Generative models for Molecular Simulations

Ersättning
Lön enligt överenskommelse

Så ansöker du
Sista dag att ansöka är 2023-05-29
Klicka på denna länk för att göra din ansökan

Omfattning
Detta är ett heltidsjobb.

Arbetsgivare
Chalmers Tekniska Högskola AB (org.nr 556479-5598)

Jobbnummer
7699003

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