Objective:

Micro- and nano pipettes are powerful and versatile sensing tools used for single-molecule detection, monitoring processes in biological systems, and as scanning probes for studying surface properties with nanoscale resolution. In this project, we are interested in the development of new nanoscience methodology, especially by investigating the image formation mechanism of scanning ion-conductance microscopy and by formulating new imaging routines that allow functional surface characterisation on the nanoscale.
Potential research directions include: finite element simulations for a better fundamental understanding of image formation; characterisation of charge density in lipid membranes and live cells; studying ion diffusion in the porous structure of hydrogels.

Qualifications:

We are looking for a motivated candidate with a master’s degree (or an equivalent university degree) within Applied Physics, Nanoscience, Materials Science or similar.
Previous experience with scanning probe microscopy is highly welcomed but not a prerequisite. Expertise in electrochemistry, cell culture and finite element modelling are also of value.

Objective:

The objective of the project is to develop and optimize a high-speed nanoscale mechanical property mapping of soft matter in their native condition. Soft matter involves a wide variety of materials ranging from polymer blends, biomolecules and live cells. The results of the project will have implications in different societal challenges such as energy storage, sustainability and health. The project will involve AFM methods, artificial intelligence, instrumentation and materials preparation.

Qualifications:

Graduate studies in Physics or Engineering (mechanical, materials or related).

Objective:

We seek a highly motivated PhD candidate to work with the development of multi-modal cell stimuli systems. The objective of the project is to develop a unique system that can realise mechanical, electrical and biochemical cell stimuli, while deciphering the role of different factors such as the mechanics, porosity, chemical composition, presence of integrin binding sites and viscoelastic properties of the scaffold in dictating the stem cell differentiation. Potential research directions include: development of a novel piezoelectric cellulose nanocrystal system for cell mechanotransduction; establishing advanced sensing, measurement, actuation and control methodologies for precision mechanical stimulation and characterisation; development of a picobalance based on a photothermally excited cantilever to link cell mass to cellular state and morphology.

Qualifications:

• Master or equivalent in biotechnology, biomedicine, molecular biology, nanotechnology or materials science.
• Good knowledge in biochemistry and cell culture. 
• Good Communication and Writing Skills in English Language.

Objective:

Electrochemistry is a field that enables the probing and manipulation of soft matter, which is becoming increasingly important in the context of societal electrification. Examples include the production of green hydrogen and the utilization of water in salt electrolytes for energy storage or conversion devices, both of which involve understanding liquid/liquid or solid/liquid/gas interfaces influenced by electrochemical processes.
In this study, and within the context of soft matter for energy applications, we will utilize nanoscale electrochemical methodologies to investigate soft matter at the level of individual micro/nano objects. However, to unveil the complexity of these objects, such as the growth, motion, or deformation of liquid nanolayers, drops, bubbles, or polymer microgels, nanoscale electrochemistry techniques need to be integrated with complementary in situ information. We will leverage our platform of refractive-index-based optical microscopies, including interference reflection and interference scattering (iSCAT) microscopies, to image and quantify in situ or operando the physical and chemical phenomena associated with the electrochemical triggering or interrogation of soft matter objects at high throughput.

Qualifications:

A master’s degree (or equivalent) in a relevant field.

Objective:

The objective of this project is the implementation and optimization of a new broadband electrostatic force microscope for fast acquisition of electrical properties (permittivity and loss/ conductivity) in a wide frequency range from kHz to GHz. The aim is to acquire full electrical spectra of the sample under study during one AFM image, which requires synchronized high-speed data acquisition and storage while standard imaging. In an initial step the system will be optimized for operation in air environment. In a second step also in-liquid measurement will be implemented.

Qualifications:

A master’s degree (or equivalent) in a relevant field.

Objective:

One objective of our research is to develop untethered (wireless) tools with which one can penetrate tissue and achieve targeted delivery of therapeutics and genetic material. The aim of this project is to develop hybrid micro- nano-robotic systems that are controlled by magnetic, acoustic, or chemical fields and that can address one or several of the following challenges:

• Generate forces and penetrate tissues effectively.
• Function as a sensor to probe cells, and the structure of tissues.
• Implement the ability to sense chemical gradients and to autonomously navigate.
• Achieve the assembly of cellular systems into ‘living machines’.
• Aid the development of minimally-invasive surgical tools.

Our research typically starts with a physical effect that we study to then develop tools and experimental systems at the micro- and nano-scale.

Qualifications:

We are looking for a motivated candidate with a master’s degree (or an equivalent university degree) in the fields of Physics, Applied Physics, Engineering, Nanoscience, Materials Science or a related discipline. A willingness to undertake high-risk high-gain experimental research is essential, as is a fascination and interest in experimental research coupled with a curiosity in biophysical questions. Previous experience with experimental research is beneficial.

Objective:

The objective of this DC project is to develop nanopipette delivery-based nanoparticle (nanorobot) therapy for single cells. The multifunctional nanopipette technique will be developed for nanoparticle release and manipulation within single cell. Multiphysical field finite element modelling and molecular dynamics simulation methods will be utilised to explore the intrinsic mechanisms acting within the nanopipette delivery and manipulation. The intelligent vision-based trajectory tracking will be established and experimentally validated.

Expected Results:
Development of multifunctional nanopipette suitable for nanoparticle delivery and manipulation within single cell. In-depth understanding of the intrinsic mechanisms underpinning the nanopipette delivery. Enhanced nanoparticle tracking techniques for the nanopipette manipulation. Precise nanomedicine for single cells.

Qualifications:

Applicants should have relevant qualifications within Nanorobotics, Applied Physics, Nanoscience, Materials Science or similar.
Previous experience with scanning probe microscopy is highly welcomed but not a prerequisite. Expertise in electrochemistry, finite element modelling, molecular dynamics simulation and machine learning are also of value.

Objective:

This study focuses on the development of nanopipettes for 2 major applications: (1) we shall make an intelligent nanopipette probe imaging platform to facilitate autonomous imaging and manipulation of cells and soft matter. The instrument will integrate an x,y,z piezo positioning system with an inverted microscope that will read optical images to identify regions of interest for investigation or intervention by the nanopipette. The instrument will be based on an existing LabVIEW FPGA architecture and incorporate machine learning protocols. It will be applicable to SICM and other forms of nanopipette probe microscopy (scanning electrochemical cell microscopy and variants thereof); (2) the use of nanopipettes and nanopore arrays for the synthesis of soft nanobots, through the development of a platform that makes use of nanoscale electric fields for mixing reagents and with active (feedback) control in the synthesis process.

Expected Results:
1) An innovative platform for functional nanopipette imaging that will have wide applicability for which the software will be made freely available to the academic community as part of the Warwick Electrochemical-Scanned Probe Microscope; 2) A synthesis platform that will enable the creation and analysis of tailored soft materials with built in functionality for applications as nanobots.

Qualifications:

Applicants should have relevant qualifications within Electrochemistry, Applied Physics, Nanoscience, Materials Science or similar.
Previous experience with scanning electrochemical microscopy is highly welcomed but not a prerequisite. Expertise in NI Labview programming, finite element modelling, and artificial intelligence for image processing is also of value.

Objective:

The objective of the DC project is to investigate fundamental, nanoscale properties of multivalent biopolymer partners undergoing liquid-liquid phase separation (LLPS), an emerging mechanism for membrane-less biological organization and cascading mesoscale structure formation. The project involves development of label-free quantitative imaging procedures, and combine these with other advanced fluorescence based optical imaging and force spectroscopy to elucidate impact of molecular and environmental parameters on LLPS.

Qualifications:

A master’s degree (or equivalent) in a relevant field.

Objective:

• Development of a deep learning algorithm assisted platform for material research
• Fast screening of biomolecular interactions
• Fast screening of biomaterial performance
• Develop mathematical relation between biomaterial binding type and surface properties

Expected Results:

• Deep learning-based analysis of fingerprint-like drying droplet patterns by training of convolutional neural networks (CNN)
• Preparation of model biomaterial surfaces using systematic variation of surface chemistry via vapour deposition polymerization of functionalized poly-p-xylylenes
• CNN extracts cellular localization patterns in polarized light microscopy (PLM) images via end-to-end hierarchical feature representations

• Screening of biomolecular interactions (e.g. DNA-protein or drug interactions)
  • classify biomolecule interaction levels to predict the optimal ratio for binding between two particular species
  • optimize and re-define the pretrained CNN to achieve more data from the images obtained by PLM imaging method
  • Scalable and accurate detection schemes for stratification of conformational and structural biomolecule alterations
• Screening of biomaterial performance via investigation of biomolecule-surface interaction via droplet patterns
  • classify biomolecule interaction to predict biomaterial binding/adhesion properties
• complementary characterization via elaborate techniques (e.g. Circular Dichroism, Time-of-Flight Secondary Ion Mass Spectrometry, Imaging Ellipsometry)
• improve model management to ensure reproducibility by avoiding information loss

Qualifications:

• Master or equivalent in chemistry, chemical engineering or materials science.
• Profound knowledge in biochemistry, polymer chemistry and physical chemistry
• Practical experience in software programming and/or scripting
• Excellent communication and writing skills in English Language

Objective:

The objective of this DC project is to establish a high speed SR SIM and expand it for multi-color and video rate super-resolved imaging of cells. Using spot-scanning SR SIM with multiple foci produced with improved microlens arrays (e.g. metasurfaces) and scanned across the sample with galvanometric mirrors, the improved imaging resolution can reach up to 80 nm and more than 230 frames for 512×512 pixel region of interest. Based on a Windows+RTX architecture, a raw data acquisition, and CMOS camera control, and on-the-fly 3D image reconstruction and display system will be established and validated based on traditional Wiener deconvolution method. The iterative (Hessian matrix based) deconvolution approach will be utilized obtain super-resolved 3D images during the post-processing steps.

Qualifications:

We are looking for an enthusiastic student with a master’s degree (or equivalent) in fields such as engineering or physics, with an understanding of optical microscopy.