Open Positions

Overview

Solid-state nanopore-based biosensors are at the frontier of single-molecule, label-free sensing and characterisation. However, where on the one hand fast translocation times enable high-throughput screening, on the other hand they pose significant challenges as for the sampling rates required to identify molecular signatures.

Furthermore, a mechanically actuated nanopore gives the additional freedom of controlling the size of the pore, hence to tune its sensitivity to features of molecules of certain dimensions; to capitalise on this opportunity, control algorithms need to be able to react in real time while the analyte is still dwelling in the sensing region. We aim to tackle this challenge by implementing our controller onto FPGA fabric in a fully automated setup where nanopositioners are to respond to electrical signatures of translocations with very low latency.

Additional challenges come from the integration of acquisition devices and related equipment (high-speed camera and laser, AC and DC amplifiers), each operating at different sampling rates, with different interface options and within different clock domains.

Ultimately we aim to build a unified data acquisition and control system capable of abstracting from these and more implementation considerations without sacrificing the performance of its components and retaining the flexibility to be easily adapted to different experimental setups.

Project goals

Students will have the opportunity to gain hands-on experience with high-end acquisition and control devices. Given the multimodal nature of the equipment, each student project can be tailored to focus on specific components of the setup and multiple projects can take place concurrently and independently.

Regardless of the specifics of each project, fundamental goals are:

1. Development of real-time control algorithms for the component of choice
2. Integration of relevant event logging into the existing infrastructure (and optional optimisation)
3. Development of suitable testbenches for validating the implemented function against arbitrary inputs
4. (Optional, dependent on progress) Testing on real experimental use-cases

Student profile

We seek highly motivated, independent students with a strong engineering background willing to give their critical contribution to the research carried out in the group.

Project type

Master thesis, semester project, bachelor thesis.

Required skills

• Git
• Python
• Basic C/C++
• (Project-dependent) System Verilog and Vivado (at least VLSI 1 or equivalent knowledge)

Desired skills

• LabVIEW
• 3D modelling
• Data / image analysis

Contact

Interested students should email indicating background, specific interests, type of project, desired start date and attach their CV and transcript of records.

Overview

Interfacial nanopores offer a flexible platform for single-molecule analysis of complex biological samples, overcoming key limitations of traditional solid-state nanopores. This project focuses on the experimental characterization and application of on-chip nanopores integrated within a microfluidic and FPGA-based system. The student will investigate the influence of physicochemical parameters on nanopore behavior and perform measurements on diverse analytes, including DNA, proteins, and nanoparticles, to assess sensitivity and extract molecular signatures. The project may also involve advanced modalities such as fluorescence imaging and contribute to the validation of emerging system functionalities. This work aims to advance the experimental capabilities and applications of nanopore-based sensing.

Description

Introduction

Solid-state nanopores have the potential to become an established technology for the analysis of highly diluted biological samples with single-molecule sensitivity. Challenges hindering their widespread use include their fixed size – which renders them specific only to the subset of molecules with comparable size and therefore only optimally suited to monodispersed samples – and the fast translocation times of molecules, which limit their ability to fingerprint them. Interfacial nanopores have recently emerged as candidates to overcome these challenges. Their controllable size across the submicron range makes them suitable to measure complex, polydispersed biological samples with lower risk of clogging, while allowing to increase translocation times by finetuning their size to that of the analyte of interest.

At BMC, we have been leveraging the low-latency processing of custom FPGA algorithms and the advantages of microfluidic platforms (lower volume, scalability, opportunities for serialization and parallelization) to bring interfacial nanopores on-chip and integrate them with a multimodal acquisition and control system including low-noise current measurements, optics, nanometre-resolution mechanical actuation and fluidics.

As the technology continuously evolves, experimental tests are required to validate it and to address research-relevant questions. This project revolves around designing, optimizing and carrying out experiments with the on-chip nanopore platform.

Project goals

To familiarise with the experimental setup, the student will begin by characterising the nanopore in buffer solution under varying conditions, including:

• Salt concentration
• Surface activation
• (Cycling) pore size
• (Cycling) pore bias

Afterwards, the student will perform recordings on analytes of interest, aiming to (i) characterize the sensitivity of the nanopore and (ii) identify signatures allowing to extract information on the sample. Analytes may include:

• Single- and double-stranded DNA of varying length
• Proteins
• Gold nanoparticles
• Vesicle-containing cellular culture medium

The student may provide experimental validation to parallel projects aiming to improve and expand the range of functionalities of the data acquisition and control system.

Depending on progress in the development of the system, the student may also conduct real-time fluorescence imaging of the nanopore in operation while sensing tagged analytes, or in presence of cellular cultures within the microfluidic platform.

Learning outcomes

Learning outcomes resulting from the successful completion of this project include:

• Hands-on experience employing solid-state nanopores to analyse biological samples with single-molecule resolution
• Ability to operate safely and according to best practices in a wet lab, including preparation and handling of BSL1 biological samples
• Ability to operate high-end hardware comprising nanopositioners, low-noise current amplifiers, microscope, high-speed camera and laser sources
• Ability to critically assess experimental results and plan, prepare and conduct study extensions accordingly
• Ability to coordinate efforts in a highly multidisciplinary team

Required skills

No prior wet lab experience is required.

Desired skills

• Python for data analysis

Assessment

Assessment criteria include but are not limited to: effort, commitment, independence, methodology, initiative, thoroughness, quality of results, documentation, final presentation and report.

Deliverables

The student will be required to submit a scientific report of their project and present it to laboratory members according to lab guidelines.

Contact

Interested students should email indicating background, specific interests, type of project, desired start date and attach their CV and transcript of records.

Keywords: interfacial nanopores, solid-state nanopores, single-molecule sensing, experimental characterization, microfluidics, FPGA, nanopore sensing, translocation dynamics, DNA analysis, protein detection, nanoparticles, fluorescence imaging, biosensing, lab-on-chip, wet lab experimentation

Overview

Interfacial nanopores enable single-molecule analysis of complex biological samples, addressing key limitations of traditional nanopores. This project develops a modular and scalable data analysis pipeline for multimodal nanopore measurements on a microfluidic platform. The work includes signal processing, event detection, feature extraction, and data visualization, with opportunities for cluster computing and machine learning approaches. The project aims to improve the robustness and scalability of nanopore data analysis for single-molecule sensing.

Description

Introduction

Interfacial nanopores are emerging as a powerful platform for the analysis of highly diluted biological samples with single-molecule sensitivity. Their controllable size across the submicron range enables the measurement of complex, polydispersed samples with reduced risk of clogging and increased translocation times, improving the ability to fingerprint individual molecules.

At BMC, we are developing an integrated on-chip platform combining interfacial nanopores, microfluidics and custom FPGA-based acquisition and control hardware. The experimental setup includes low-noise current measurements, optics, nanometre-resolution mechanical actuation and fluidics, enabling multimodal measurements and rapid exploration of new sensing strategies.

This project combines experimental work with data science and signal processing. The student will work directly with measurements generated by the nanopore platform to develop and validate analysis tools that improve the extraction of information from single-molecule recordings. The project offers the opportunity to interact closely with the experimental setup, understand how measurements are acquired and use this understanding to design robust and interpretable analysis workflows.

As the measurement system continuously evolves and new sensing modalities emerge, there is a growing need for a standardised, modular and scalable data analysis pipeline that remains aligned with the state of the art in nanopore signal processing and interpretation.

Project goals

The student will begin by familiarising themselves with the experimental setup and the characteristics of nanopore measurements across different acquisition modalities and protocols. Initial work will focus on understanding experimental constraints and identifying opportunities to improve analysis and interpretation.

Building on experimental observations, the student will develop and extend data analysis tools for emerging data modalities and new experimental protocols while researching and implementing state-of-the-art algorithms. Areas may include denoising, event detection, time-series alignment, feature extraction, clustering, statistical analysis and visualisation.

The student will iteratively validate analytical methods on experimentally acquired datasets and refine tools to support reproducible and interpretable research workflows. Visualization and reporting methods will also be standardised and adapted to different experimental questions.

As data throughput increases with platform scaling, the student is encouraged to develop pipelines that leverage cluster computing and efficient processing strategies. Investigation of machine learning methods for nanopore analysis is welcome where appropriate.

Because fully automated pipelines may overlook unexpected or out-of-distribution phenomena that could carry scientific value, the student will explore strategies for semi-supervised analysis, interactive review and intelligent data compression. Depending on interest and project scope, the project may also include integration of analysis pipelines into the custom web graphical user interface used to control and monitor on-chip nanopore experiments.

For master theses, experimental work forms an integral part of the project: students will perform measurements on the nanopore setup to validate new acquisition protocols and analytical tools. Bachelor thesis and semester project students may also participate in experiments if desired. No prior wet lab experience is required.

Learning outcomes

Learning outcomes resulting from the successful completion of this project include:

• Ability to critically assess research needs and optimize and test data analysis pipelines accordingly
• (Optional) Ability to operate safely and according to best practices in a wet lab
• Ability to interpret data from a heterogeneous data acquisition and control setup comprising high-end hardware including nanopositioners, low-noise current amplifiers, microscope, high-speed camera and laser sources
• Experience developing data analysis algorithms with immediate impact on research outcomes
• Ability to coordinate efforts in a highly multidisciplinary team

Required skills

• Git: basic
• Python: proficient

Desired skills

• C/C++ (project-dependent)
• Image analysis

Assessment

Assessment criteria include but are not limited to: effort, commitment, independence, methodology, initiative, thoroughness, quality of results, documentation, final presentation and report.

Deliverables

The student will be required to submit a scientific report of their project and present it to laboratory members according to lab guidelines.

Contact

Interested students should email indicating background, specific interests, type of project, desired start date and attach their CV and transcript of records.

Keywords: interfacial nanopores, solid-state nanopores, single-molecule sensing, biological samples, microfluidics, FPGA, multimodal acquisition, data analysis pipeline, signal processing, denoising, event detection, time-series alignment, feature extraction, clustering, statistical analysis, data visualization, machine learning, semi-supervised learning, big data, cluster computing, real-time monitoring, web interface, nanotechnology

Overview

Interfacial nanopores integrated in microfluidic platforms offer a versatile approach for single-molecule sensing, but their design and optimization require detailed physical understanding. This project focuses on developing finite element models of on-chip nanopore systems to simulate mechanical, fluidic, and electrochemical behavior. The student will use these simulations to guide chip design, optimize performance, and reduce experimental trial-and-error. Model predictions will be compared with experimental results from in-house fabricated devices, with potential extensions to novel actuation strategies and scalable microfluidic architectures. This work aims to accelerate the development and optimization of nanopore-based sensing technologies.

Description

Introduction

Interfacial nanopores are emerging as a powerful platform for the analysis of highly diluted biological samples with single-molecule sensitivity. Their controllable size across the submicron range enables the measurement of complex, polydispersed samples with reduced risk of clogging and increased translocation times, improving the ability to fingerprint individual molecules.

At BMC, we are developing an integrated on-chip platform combining interfacial nanopores, microfluidics and custom FPGA-based control and acquisition hardware. The experimental setup includes low-noise current measurements, optics, nanometre-resolution mechanical actuation and fluidics, enabling multimodal characterization of nanopore behavior and rapid testing of new device concepts.

This project combines computational modelling with hands-on experimental validation. The student will contribute to the design and optimization of next-generation nanopore chips and directly evaluate their performance using our in-house fabrication and measurement infrastructure. Experimental measurements will be used to validate predictions, guide design decisions and investigate novel research questions.

To support this process, the student will develop mechanical and fluidic models of on-chip nanopore systems to predict and interpret experimental observations and accelerate design iterations.

Project goals

The project will start with familiarisation with the experimental platform and the operation of on-chip nanopore systems. The student will carry out measurements and characterization procedures to gain intuition about device behaviour and identify key experimental constraints.

Building on these observations, the student will design and implement finite element models and simulations of nanopore microfluidic chips to support experimental procedures and interpret empirical results. Simulations may include solid mechanics, fluidics, electrochemistry and related multiphysics phenomena.

Insights from simulations will then be used to optimize new chip designs and reduce the design search space before fabrication. Thanks to rapid in-house manufacturing capabilities, the student will have the opportunity to experimentally validate model predictions on newly fabricated nanopore chips and iteratively refine both models and designs.

Depending on the duration and agreed scope of the project, the student may further investigate novel actuation strategies for the formation and control of interfacial nanopores, as well as new microfluidic architectures addressing research questions such as serialization, parallelization and integration with cell cultures.

For master theses, experimental work forms a core component of the project: students will conduct measurements on the experimental setup to validate new designs and verify predictions. Bachelor thesis and semester project students may also participate in experiments if desired. No prior wet lab experience is required.

Learning outcomes

Learning outcomes resulting from the successful completion of this project include:

• Ability to critically assess research needs and develop and test finite element models and simulations to address them
• (Optional) Ability to operate safely and according to best practices in a wet lab
• Ability to iterate on simulations and empirical observations to optimize frontier research tools
• Experience designing experimental platforms with immediate impact on research outcomes
• Ability to coordinate efforts in a highly multidisciplinary team

Required skills

• COMSOL or equivalent
• 3D modeling

Desired skills

• Python for data analysis

Assessment

Assessment criteria include but are not limited to: effort, commitment, independence, methodology, initiative, thoroughness, quality of results, documentation, final presentation and report.

Deliverables

The student will be required to submit a scientific report of their project and present it to laboratory members according to lab guidelines.

Contact

Interested students should email indicating background, specific interests, type of project, desired start date and attach their CV and transcript of records.

Keywords: interfacial nanopores, solid-state nanopores, finite element modeling, COMSOL, microfluidics, lab-on-chip, simulation, fluid dynamics, solid mechanics, electrochemistry, device design, optimization, nanopore sensing, multiphysics modeling, biosensing