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PhD Positions at The University of Manchester

1.  2D materials based-membranes for biomedical applications

Application Deadline: Applications accepted all year round... Students Worldwide

Details

Chemical separations are critical to many aspects of our daily lives, from the energy we use and the water we drink, to the medications we take. Separations consume 10-15% of the total energy used in the world, and high selectivity membranes could make these separations 10-times more energy efficient. In this project, you will be involved in the development of high selectivity membranes using 2D materials such as graphene for biomedical applications. The aim of the project is to develop membranes that be implemented in the pocket-sized biosensors for fast diagnosis of some types of diseases.


 This PhD studentship is provided by the University in support of a programme of research that links membrane researchers at six universities (Manchester, Bath, Edinburgh, Newcastle, Imperial College London, Queen Mary University of London). The research is funded through a Programme Grant from the Engineering and Physical Sciences Research Council (EPSRC) entitled “Membrane Material Synthesis for High Selectivity” (SynHiSel). Our vision is to create the high selectivity membranes needed to enable the adoption of a novel generation of emerging high-value/high-efficiency membrane processes.

Entry Requirements


Applicants are expected to hold, or be about to obtain, a minimum upper second class MChem/MEng or MSc degree (or equivalent) in Chemistry or Chemical Engineering. They should have excellent laboratory skills for polymer synthesis and materials characterization, and should clearly understand aspects of materials science and engineering relevant to the development of membrane materials. The successful candidate will have exceptional team-working and communication skills, so as to interact effectively with other researchers at Manchester and collaborating Universities.


Application Information


Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/. Please make contact with the lead project supervisor before submitting an application.


When completing the application include the name of the lead project supervisor as the potential supervisor.


Enquiries about this project can be sent to Dr Maria Perez-Page - maria.perez-page@manchester.ac.uk as the lead project supervisor. The Admissions team in Chemical Engineering can be contacted at pgr-admissions-chemeng@manchester.ac.uk with any queries you may have regarding the application process.


Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.


We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).


Funding Notes

This is a 3.5 years fully funding project.


APPLY HERE

2.  Application of deep learning to characterise transport of waste-derived gas in Lower Strength Sedimentary Rocks (LSSRs)

Application Deadline: 01 August 2022.....  Students Worldwide

Details

This is a 4-year PhD project funded by Nuclear Waste Services after a competitive call for PhD bursary. The topic of research is on use of machine learning for characterising the complex transport of gas in LSSRs. Hydrogen developed from anaerobic corrosion of the steel canisters and other iron-containing structures and from the radiolysis of water due to radioactive decay, will trigger a complex flow problem where hydrogen transports in water-saturated heterogeneous clay pore space. Different physical processes are incurred such as diffusion of H2, uptake or adsorption of the gas on rock surface, as well as interactions with clay host rock. Additionally, clays feature extensive level of mineralogical and physical (pore space) heterogeneity. Existing literature have showed that experiments and flow modelling (based on classical numerical methods) of these processes are computationally expensive. Therefore, we propose firstly to use machine learning and pattern recognition to construct a set of databases for various clay rock features. This will be done in tandem with x-ray microtomography and utilising existing literature images.


Main objectives:


Stochastic compilation of a large database of machine learning, pattern recognition and x-ray micro-CT based realisations of clay rock mineralogical and pore space maps for use in modelling.

Image based modelling of single and two-phase waste-derived gas transport in water for sedimentary rock samples.

Deep learning (Convoluted Neural Network)-based characterisation of regimes of gas transport (adsorption/uptake, diffusion and reactive with surrounding clay) in single- and two-phase conditions for varying rock minerals and pressure and temperature.


Machine learning-based risk analysis of long-term radionuclides fate within multiscale mineralogically heterogeneous clay systems with various pore features specific to clay.

Entry Requirements


UK applicants with 2:1 and above GPA in civil, chemical, fluid mechanics or computer engineering are invited to apply.


Applicants should demonstrate research capability in computational modelling, programming with Python or C++ and have knowledge of AI and machine learning, numerical methods and computer programming, and simulations related to porous media and fluid dynamics.


Application Information


We strongly recommend that you make contact with your proposed supervisor before submitting an application. Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/. To apply for this project, select PhD Chemical Engineering and then PhD Multi-scale Modelling. Take note of the application checklist and provide the requested documents. When completing the application include the name of the lead supervisor as the potential supervisor.


Enquiries about this project can be sent to Dr Masoud Babaei - masoud.babaei@manchester.ac.uk as the lead project supervisor. The Admissions team in the Department of Chemical Engineering can be contacted at pgr-admissions-chemeng@manchester.ac.uk with any queries you may have regarding the application process.

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.


We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder). 


Funding Notes

Funded for 4 years by Nuclear Waste Services for UK students only.


APPLY HERE

3. Engineering Downstream Processes to Enhance Processability of Crystallized Products

Application Deadline: Applications accepted all year round....  Students Worldwide

Details

What is the PhD Project About?


This project, performed in collaboration with AstraZeneca, will address one of the key challenges in processing pharmaceutical products. In the production chain of active pharmaceutical ingredients (API), a crystallization step is an integral part for separation and purification purposes. A typical solution crystallization step is followed by the so-called downstream processing steps. These correspond to a solid-liquid separation step, i.e. filtration, a washing step to remove the mother liquor from the filter cake, and finally a drying step to evaporate the wash solvent. The dried powder is eventually blended with excipients and in some cases formulated as tablets or granules to obtain the final solid product. The performance of these steps is often dictated by the crystallization step, namely through the particle size and shape distribution (PSSD), the moisture content, the surface properties (e.g. cohesive/adhesive interactions), to name a few, of the crystallized product. The aforementioned downstream steps have been studied both experimentally and computationally in detail for many different applications. Experimental and modeling studies that aim to provide an empirical relationship between the PS(S)D (mostly on size and rarely on shape) and the final filter cake porosity have been reported. Despite the significance of PSSD, washing and drying have been scarcely explored over the years, especially in an integrated framework with the upstream crystallization step.

How Will this Challenge be Addressed?


To address the challenge related to engineering downstream processes, we will develop an innovative multiscale research campaign. We will capitalize on the state-of-the-art experimental (microscopic and multiprojection imaging devices, agitated filter-dryer, tomographic devices) and computational tools (population balance equation solvers, parameter estimators, molecular modeling, packed bed models), readily available at the University of Manchester. In particular, we will develop predictive microscopic and macroscopic models backed by experimental data for all the three aforementioned downstream steps (filtration, washing and drying) to improve our understanding and in turn develop efficient processes. These models will pave way to integrate the entire process chain, where given a PSSD one could quantitatively gauge the processability of the crystallized product in terms of both processing time and energy consumption.


Supervisory Arrangements for the PhD Student and the Environment


The PhD student will be jointly supervised by Dr. Ashwin Kumar Rajagopalan, Lecturer and Dr. Carlos AvendaƱo, Senior Lecturer, both in the Department of Chemical Engineering at the University of Manchester. The project is an industrial CASE studentship, hence the PhD student will also work closely with our industrial project, AstraZeneca with the student spending 3 months at the company site to get exposed to industrial research. The PhD student will also work in a tight collaboration with PhD students and postdoctoral research associates from both the groups. The student will have access to the laboratory facilities of the group in the newly opened Engineering Building (part of the MECD program) at the University of Manchester. The student will also have access to the computational shared facility, a 10000 node cluster and one of the best in the world, to tackle the computational aspects of this project.


What can the PhD Student Expect?


Disseminate results obtained over the course of the PhD program through prestigious peer-reviewed journals (e.g. Chemical Engineering Science, Chemical Engineering Journal, Crystal Growth & Design, Powder Technology, Separation and Purification Technology, etc.,)

Attend national (British Associate of Crystal Growth) and international (International Symposium on Industrial Crystallization, American Institute of Chemical Engineering Annual Meeting etc.,) scientific conferences and workshops (EFCE summer schools on crystallization) across the globe to present research findings and network with peers from academia and industry

Work with a young and growing research group at the birthplace of chemical engineering

Have the opportunity to collaborate with other research groups working on relevant topics at the University of Manchester

Have access to several one-of-a-kind experimental and computational tools in the UK, that has the potential to be transferred to an industrial setting in the near future

Get direct exposure to industrial partners through this project and indirect exposure through projects of other PhD students in the research group

Obtain a PhD degree on solving classical chemical engineering problems and learn and hone 21st century experimental and computational skills that can be readily transferrable to both an academic and an industrial setting


Entry Requirements


Applicants should have or expect to achieve a first-class honours degree in Chemical Engineering or Process Engineering. Under exceptional circumstances, high 2.1 applicants will be considered.


Application Information


Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/. Please make contact with the lead project supervisor before submitting an application.

When completing the application include the name of the lead project supervisor as the potential supervisor.


Enquiries about this project can be sent to Dr Ashwin Kumar Rajagopalan - ashwinkumar.rajagopalan@manchester.ac.uk as the lead project supervisor. Applicants can also visit ash23win.github.io for further information regarding Dr Rajagopalan’s research group. The Admissions team in Chemical Engineering can be contacted at pgr-admissions-chemeng@manchester.ac.uk with any queries you may have regarding the application process.


Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.


We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder). 


Funding Notes

This is a 3.5-year studentship that will ideally support a start in September 2022. The funding will provide a tax-free stipend to cover living costs (UKRI-standard stipend rate is £16,062 for 2022/23).


APPLY HERE

4.  Process Development for Size and Shape Manipulation of Elongated Crystals

Application Deadline: Applications accepted all year round....  Students Worldwide

Details

What is the PhD Project About?


This project will address one of the key challenges in crystallization process development. Crystallization is a separation and purification technique that is widely employed in pharmaceutical, agrochemical, and fine chemical industries. In pharmaceuticals, Active Pharmaceutical Ingredients, that are solid at ambient temperature and pressure, undergo at least one or more crystallization steps in their production chain. The crystallization step leads to particulate matter (or powders), composed of an ensemble of crystals exhibiting a plethora of sizes and shapes, described by the so called Particle Size and Shape Distribution (PSSD). It is well known that the PSSD is a major factor in dictating the downstream processability (e.g. filterability, flowability, tabletability) of a powder. Process alternatives, incorporating chemical engineering unit operations, can be employed to manipulate the PSSD and steer it toward a more favorable one. Finding novel process alternatives to tackle the issues related to PSSDs is a very relevant area of research for many industrial processes incorparting a crystallization step. Any improvements made along these lines will aid in reducing product wastage and energy consumption of the entire production chain. This in turn reduces the final cost of the product (e.g. drugs, fertilizers) in question and makes the entire process more sustainable.

How Will this Challenge be Addressed?


To address the challenge related to the manipulation of PSSDs, we will develop an innovative research campaign, capitalizing on the state-of-the-art experimental (microscopic and multiprojection imaging devices) and computational tools (population balance equation solvers and parameter estimators), readily available at the University of Manchester. In particular, we would like to explore the role of additives, which have the potential to restrict growth of crystals to certain shapes, to produce crystals with favorable PSSDs. To this aim, we will develop a process in a batch/semi-batch configuration, as would be typically done in an industrial setting. Digital twins of the process will be developed to complement the experimental evaluation of the processes developed during the course of this work. Additionally, new avenues in mathematical modeling of chemical processes involving a combination of physics-based and machine learning methodologies will be explored.


Supervisory Arrangements for the PhD Student and the Environment


The PhD student will be supervised by Dr. Ashwin Kumar Rajagopalan, Lecturer in the Department of Chemical Engineering at the University of Manchester. The PhD student will also work in a tight collaboration with PhD students and postdoctoral research associates from the group of Dr. Aurora Cruz-Cabeza. The student will have access to the laboratory facilities of the group in the newly opened Engineering Building (part of the MECD program) at the University of Manchester. The student will also have access to the computational shared facility, a 10000 node cluster and one of the best in the world, to tackle the computational aspects of this project.


What can the PhD Student Expect?


Disseminate results obtained over the course of the PhD program through prestigious peer-reviewed journals (e.g. Chemical Engineering Science, Chemical Engineering Journal, Crystal Growth & Design, etc.,)

Attend national (British Associate of Crystal Growth) and international (International Symposium on Industrial Crystallization, American Institute of Chemical Engineering Annual Meeting etc.,) scientific conferences and workshops (EFCE summer schools on crystallization) across the globe to present research findings and network with peers from academia and industry

Work with a young and growing research group at the birthplace of chemical engineering

Have the opportunity to collaborate with other research groups working on relevant topics at the University of Manchester

Have access to several one-of-a-kind experimental and computational tools in the UK, that has the potential to be transferred to an industrial setting in the near future

Get exposure to industrial partners through projects of other PhD students in the research group

Obtain a PhD degree on solving classical chemical engineering problems and learn and hone 21st century experimental and computational skills that can be readily transferrable to an both academic and an industrial setting


Entry Requirements


Applicants should have or expect to achieve a first-class honours degree in Chemical Engineering or Process Engineering. Under exceptional circumstances, high 2.1 applicants will be considered.


Application Information


Information about the application process and a link to the online application form can be found at https://www.manchester.ac.uk/study/postgraduate-research/admissions/how-to-apply/. Please make contact with the lead project supervisor before submitting an application.


When completing the application include the name of the lead project supervisor as the potential supervisor.

Enquiries about this project can be sent to Dr Ashwin Kumar Rajagopalan - ashwinkumar.rajagopalan@manchester.ac.uk along with your CV and cover letter. Applicants can also visit ash23win.github.io for further information regarding Dr Rajagopalan’s research group. The Admissions team in Chemical Engineering can be contacted at pgr-admissions-chemeng@manchester.ac.uk with any queries you may have regarding the application process.


Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.


We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder). 


Funding Notes

This is a 3.5-year studentship that will ideally support a start in September 2022. The funding will provide a tax-free stipend to cover living costs (UKRI-standard stipend rate is £16,062 for 2022/23).

APPLY HERE

For more detail please visit the official site

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