|CCL 19.12.16 Three postdoc positions in computational chemistry and machine learning for molecular science (DTU, Denmark)|
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To: jobs at ccl.net
Date: Mon Dec 16 11:31:31 2019
Subject: 19.12.16 Three postdoc positions in computational chemistry and machine learning for molecular science (DTU, Denmark)
The Sections for Atomic Scale Materials Modelling at DTU Energy and Cognitive Systems at DTU Compute, Technical University of Denmark (DTU), are looking for outstanding candidates for three 2-year postdoc positions within the fields of computational chemistry and machine learning for molecular science. The research positions are part of the Novo Nordisk Foundation Exploratory Interdisciplinary Synergy Programme: Self-correcting Unsupervised Reaction Energies (SURE), which brings together researchers from DTU Energy and DTU Compute. Project descriptions The successful candidates will use electronic structure modelling (e.g. DFT and wave function methods) and machine learning algorithms to develop a framework for uncertainty-aware prediction of chemical reaction networks. The framework development will consist of the following postdoc projects: 1. DFT and wave function electronic structure methods will be used to calculate high-fidelity data for the thermodynamics and kinetics of selected chemical reactions. The developed methodology will be used to train the data-driven models developed in the parallel projects, as well as to validate them for the prediction of degradation reaction networks of organic electroactive molecules used in redox flow batteries. The ideal candidate will have experience in modelling of reaction mechanism of molecular systems. 2. Molecular graph operation based methods will be established and used for reaction intermediate and product candidate generation. Machine learning predicted energies of these structures will help us create probabilistic model of the reaction networks. Furthermore, new tools will be developed to provide uncertainty guided analysis on reaction products and mechanisms. Experience in scientific programming (e.g. Python) and Bayesian statistics will be advantageous. 3. Graph convolutional neural network models will be built for evaluating errors and uncertainties in molecular energies obtained from electronic structure simulations of varying complexity. Model training methods that can utilize multi-fidelity data will be incorporated. The developed framework will be utilized to predict energies for any given molecular structure along with uncertainties, to build probabilistic models for reaction networks. Experience in machine learning model development is expected. The three projects will be carried out in close collaboration between the two sections and linked to other ongoing projects in the sections working on clean energy materials and machine learning for accelerated materials discovery. Qualifications Candidates should hold a PhD or equivalent degree in computer science, physics, chemistry or materials science. The candidate must have a strong background in computational chemistry, physics or materials science and/or machine learning, and are expected to have performed original scientific research within the relevant fields listed above for the specific position(s). Moreover, the successful candidate: - is innovative and able to work both independently and in cross-disciplinary teams - has good communication skills in English, both written and spoken - is able to work independently and take responsibility for progress and quality of projects. Assessment The assessment of the applicants will be made by: Head of Section, Professor Tejs Vegge, Professor Ole Winther, Associate Professor Mikkel N. Schmidt, Assistant Professor Piotr de Silva and Researcher Arghya Bhowmik 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 appointments will be for 2 years and be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union. The employment is expected to start April 1st, 2020 or shortly thereafter. Further information If you need further information concerning these positions, please contact Prof. Tejs Vegge at teve:-:dtu.dk or Professor Ole Winther at olwi:-:dtu.dk. Please do not send applications to these e-mail addresses, instead apply online as described below. Application We must have your online application by 20 January 2020. Remember to indicate which of the positions you are applying for (not limited to one). Applications must be submitted as one pdf file containing all materials to be given consideration. To apply, please go to: https://www.dtu.dk/english/About/JOB-and-CAREER/vacant-positions/job?id=4b2ea7fc-f910-446f-93b5-3b0ad234458d open the link "Apply online," fill in 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 - BSc/MSc/PhD diploma - List of publications indicating scientific highlights - List of References (at least two) All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. DTU Energy The Department of Energy Conversion and Storage is focused on education, research, and development within functional materials and their application in sustainable energy technologies. The Department is focusing on functional materials and their application in sustainable energy technology. Our research areas include fuel cells, electrolysis, polymer solar cells, magnetic refrigeration, superconductivity, thermo electrics, sustainable synthetic fuels, and batteries. Additional information about the department can be found on www.energy.dtu.dk. DTU Compute DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavor. 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 UNs 17 Sustainable Development Goals. Hans Christian rsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.
Text of the call and application link at: https://www.dtu.dk/english/About/JOB-and-CAREER/vacant-positions/job?id=4b2ea7fc-f910-446f-93b5-3b0ad234458dNOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED!!!
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