فاند دکتری شیمی دانشگاه گرینویچ انگلستان

فاند دکتری شیمی دانشگاه گرینویچ
5/5 - (1 امتیاز)

فاند دکتری شیمی دانشگاه گرینویچ

فاند دکتری شیمی دانشگاه گرینویچ انگلستان | این پروژه مشترکاً توسط دکتر Jiayun Pang ، دکتر Xacobe C. نظارت می شود و زمینه تحقیقاتی بر روی “روشهای پایدار برای سنتز ترکیبات فعال زیستی از طریق یادگیری ماشین – کاتالیزورهای جدید برای فعال سازی انتخابی پیوندهای CH آلیفاتیک که توسط نور مرئی می باشد.

رشته‌های مرتبط:

  • شیمی آلی
  • فتوشیمی
  • الکتروشیمی
  • شیمی محاسباتی
  • رشته های مرتبط

امتیازت و مزایا:

  • سالانه ۱۵۲۸۵ پوند
  • فول تایم (هفته ای ۳۵ ساعت)

لینک اپلای:

وارد شوید

ایمیل ارتباطات:

x.cambeiro@gre.ac.uk

مهلت اپلای:

۱۴۰۰٫۰۶٫۱۹

گواهی پذیرش کبک | تغییر زمان و مرکز آزمون تافل | ارزشیابی مدرک تحصیلی در آلمان | شرایط کار دانشجویی در اتریش

PhD studentship

OFFER DESCRIPTION

A PhD studentship is available to work on the project “Sustainable methods for the synthesis of bioactive compounds through machine learning – New catalysts for the selective activation of aliphatic C-H bonds promoted by visible light“, jointly supervised by Dr Jiayun Pang, Dr Xacobe C. Cambeiro and Prof. Adrian Dobbs. The position is funded by a Vicechancellor Scholarship of the University of Greenwich, which covers a stipend in line with RCUK (currently £۱۵,۲۸۵ per year) and home student university registration fees. Applicants not eligible for home fees would need to fund the difference. If interested, contact Xacobe directly by e-mail: x.cambeiro@gre.ac.uk.

Background. C-H functionalisation methods offer an invaluable opportunity for the design of streamlined, more efficient and environmentally benign syntheses by using ubiquitous C-H bonds as reactive handles for the coupling of organic fragments. Photocatalytic C-H functionalisation of alkanes via hydrogen atom transfer (HAT) catalysis has recently emerged as a powerful strategy. However, the design of catalysts able to selectively activate a specific C-H bond in the presence of many others has been prevented by the subtle balance of variables involved. Computational approaches and in particular machine learning are emerging as powerful tools for catalyst design in related areas.

Aim. We propose here a strategy for the development of selective C-H functionalisation reactions based on using machine learning for the construction of predictive models. This approach will be demonstrated through the development of an oxidative alkylation of pyridine derivatives with O2 as the terminal oxidant, which will be used for the synthesis of valuable pyridine-containing bioactive molecules.

Environment. The student will join a vibrant team of postgraduate students and postdocs working in the synthetic and medicinal chemistry research group at the School of Science, sited at the University of Greenwich dedicated Science and Engineering campus at Medway (Kent), just over 30 min by train from central London, or 45 min from historic Greenwich with the university-operated bus service (heavily discounted for students). The team includes researchers working in photochemistry, electrochemistry and flow chemistry systems as well as more traditional synthetic methods, which provides a very diverse research and learning experience for members.

Training. The student will receive multidisciplinary training in synthesis, photocatalysis, computational chemistry and machine learning, developing a uniquely diverse set of skills of high value for their future career. Also, the student will learn to use analytical instruments such as NMR, GCMS and UHPLC as well as electrochemistry equipment. Training-by-research will be facilitated by the supervisors, and the student will have unfettered access to the University’s Research and Enterprise Training Institute for additional skills training.

Further reading.

Hydrogen atom transfer catalysis: (a) G. Laudadio, Y. Deng1, K. van der Wal1, D. Ravelli, M. Nuño, M. Fagnoni, D. Guthrie, Y. Sun, T. Noël, Science 2020, 369, 92. https://doi.org/10.1126/science.abb4688. (b) K. A. Margrey, W. L. Czaplyski, D. A. Nicewicz, E. J. Alexanian, J. Am. Chem. Soc. 2018, 140, 4213. https://doi.org/10.1021/jacs.8b00592. (c) I. B. Perry, T. F. Brewer, P. J. Sarver, D. M. Schultz, D. A. DiRocco, D. W. C. MacMillan, Nature 2018, 560, 70. https://doi.org/10.1038/s41586-018-0366-x.

Machine learning as a tool for catalyst design: (a) G. dos Passos Gomes, R. Pollice, A. Aspuru-Guzic, Trends Chem. 2021, 3, 96. https://doi.org/10.1016/j.trechm.2020.12.006. (b) W. Yang, W. Yang, T. T. Fidelis, W.-H. Sun, ACS Omega, 2020, 5, 83. https://doi.org/10.1021/acsomega.9b03673.

More Information

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Chemistry: Bachelor Degree or equivalent

Skills/Qualifications

The applicant should have or be about to obtain at least a BSc degree in Chemistry or a related area, although a Master degree is desirable. Great grades, relevant research experience and enthusiasm about science and about the project are also desirable.

کشورهایی با بیشترین بورسیه تحصیلی | روش کاهش هزینه دانشگاه خارجی | ددلاین اپلای

دیدگاه کاربران
  • ساناز 7 سپتامبر 2021 / 10:05

    جا داره بابت این به روز رسانی ها تشکر کنم

ارسال دیدگاه

نشانی ایمیل شما منتشر نخواهد شد. بخش‌های موردنیاز علامت‌گذاری شده‌اند *

توسط
تومان