Research Assistant (contractual)

Mika Meyers PLC; United States; Remote; USD 30,000 - 45,000; Full time

Job summary

A leading company in the field of neural engineering is seeking a motivated research assistant to support a clinical study involving fNIRS and EEG data analysis. Candidates should hold a strong scientific background and possess relevant skills in research and data analysis. This position not only contributes to innovative research but potentially leads to a PhD opportunity.

Qualifications

• Relevant scientific discipline like biomedical engineering, neuroscience, or computer science.
• Prior research experience and/or a Master’s degree is encouraged.
• Role may lead to a PhD opportunity.

Responsibilities

• Analyze fNIRS and EEG data as part of a clinical study.
• Assist in data collection and experimental setup for research.
• Prepare reports and participate in study evaluations.

Skills

Data analysis

Neural engineering

Research skills

Statistical analysis

Education

First-class or Upper Second-class undergraduate degree

Job description

We are currently seeking talented and motivated students with a strong interest in neural engineering, particularly in the application and analysis of functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) data. This position is part of an exciting research programme led by Dr. Anirban Dutta within the Department of Metabolism and Systems Science at the University of Birmingham. https://www.birmingham.ac.uk/staff/profiles/metabolism-systems/dutta-anirban

Project Background
Dutta et al. (2021) conducted a study on healthy volunteers at the University at Buffalo (USA), demonstrating a statistically significant (p < 0.01) increase in cerebral blood volume (CBV) following activation of the calf muscle pump using intermittent neuromuscular electrostimulation (NMES) of the common peroneal nerve via the geko device. While this device is typically used for preventing deep vein thrombosis (DVT) and pulmonary embolism post-stroke, the CBV-enhancing effects have not yet been explored in stroke patients.

Cheung, Mancheung. Hemodynamics Due to Calf Muscle Activity – Biophysical Modeling and Experiments Using Frequency Domain Near Infrared Spectroscopy in Healthy Humans. State University of New York at Buffalo, 2018. ProQuest Dissertation 10823366. https://ubir.buffalo.edu/xmlui/handle/10477/78042

Building on these promising findings, we are launching the RETRAIN Trial, a two-phase clinical study aimed at further investigating these effects in stroke survivors:

Study Overview
Phase 1 (completed): Assess the relationship between brain haemodynamics and varying NMES intensities (using the geko device) on both affected and unaffected limbs in patients with chronic ischemic stroke (>7 days post-onset).
Utilize a joint fNIRS-EEG imaging setup to evaluate cerebral responses.
Determine the optimal sensor placement for Phase 2.

Reference: https://www.medrxiv.org/content/10.1101/2025.05.10.25327353v1

Phase 2 (ongoing): Compare cerebral blood flow (CBF) improvements between the geko and intermittent pneumatic compression (IPC) devices in patients within the acute phase of ischemic stroke (<48 hours post-onset).
Sponsored by Countess of Chester Hospital NHS Foundation Trust (IRAS ID: 325629)

Applicant Requirements: Candidates should possess a First-class or Upper Second-class undergraduate degree in a relevant scientific discipline, such as biomedical engineering, neuroscience, physiology, computer science, or a closely related field. Applicants with prior research experience and/or a Master’s degree are particularly encouraged to apply for a 12-month contractual research assistant position. This role may serve as a pathway to a 3-year full-time PhD (or part-time equivalent), subject to mutual agreement and satisfactory performance during the initial contract.

To apply, please prepare and submit the following:

Curriculum Vitae (CV): Including nationality and country of birth
Cover Letter: Detailing your research experience, capabilities, and motivation to join this project
Two academic references (names and contact details)
Degree certificates and academic transcripts (in English)
Evidence of English language proficiency (if applicable)