Doctoral Candidate (Ph.D. student) position in semi-automated supercritical CO₂ drying within the Marie Skłodowska-Curie Doctoral Network “FAroGels – Food-Grade Aerogels

About this position

We are looking to admit outstanding applicant as Doctoral Candidate

(DC4 – Semi-automated Supercritical CO₂ Drying for Reproducible Structures)

at Superex (Pard Mühendislik ve Otomasyon Sanayi Ticaret Ltd. Şti.), Konya, Türkiye

. Highly motivated Ph.D. applicants are encouraged to join FAroGels, funded by the European Union under Horizon Europe – Marie Skłodowska-Curie Actions Doctoral Networks (HORIZON-MSCA-2025-DN-01-01, Grant Agreement No. 101312450). The position is a fixed-term employment contract of 36 months, full-time (100%),

with Superex as recruiting/host organisation and Selçuk University (Department of Physics, Konya, Türkiye) as PhD awarding institution.

Project summary

FAroGels brings together academic and non-academic partners with complementary expertise in food science and technology, materials science, biopolymer science, biotechnology, process engineering, analytical characterization, packaging and sustainable innovation. FAroGels aims to develop, characterize and validate food-grade, bio-based and biodegradable aerogels for sustainable food systems. The network will investigate how these highly porous materials can support more efficient food processing, improved food quality and safety, nutritional and sensory functionality, protection and delivery of bioactive compounds, and sustainable packaging solutions.

This position forms part of the FAroGels research program on food-grade, bio-based, and biodegradable aerogels and their application in sustainable food systems. The selected candidate will be employed by

Superex

and will be required to enroll as a PhD student at

Selçuk University

, in accordance with the relevant admission and enrolment requirements.

Project objectives

Food-grade aerogels can only move beyond the laboratory if they can be dried reproducibly. Supercritical CO₂ drying is the decisive production step, but laboratory dryers are still largely tuned by hand, which causes substantial batch-to-batch variability. DC4 will tackle this bottleneck by designing and building a semi-automated supercritical CO₂ drying system with real-time monitoring of pressure, temperature, CO₂ density and solvent saturation.

The data logged during drying will be used to create process datasets linking drying trajectories to aerogel density, pore-size distribution and mechanical performance. On this basis, the project will develop and validate a machine-learning control module, trained first on commercial reference materials and then on aerogels produced elsewhere in the network, such as seaweed-residue aerogels and aerogels from non-gelling biopolymers. The AI-assisted system will recommend optimised temperature, pressure and depressurisation profiles, reducing trial-and-error and improving reproducibility and efficiency.

The Doctoral Candidate will contribute to equipment design and instrumentation, run drying experiments, analyse process and structural data, and translate the results into standardised drying protocols for the network. The expected outcomes are a functional semi-automated dryer with full sensor integration and data logging, parameter–property datasets, a trained control model, and drying SOPs used across FAroGels. DC4 is one of the enabling projects of the network: it supplies aerogels with controlled, documented structures and consistent materials for the food, packaging and modelling projects.

The position will involve laboratory-based research, data analysis, scientific communication and close collaboration with other FAroGels Doctoral Candidates, supervisors and partner organizations.

Main responsibilities

Conduct research on the design, instrumentation and operation of a semi-automated supercritical CO₂ drying system and on data-driven control of the drying process for reproducible aerogel structures.

Plan, perform, document and analyse experimental work using relevant laboratory, analytical, processing and/or modelling methods.

Collaborate with academic and non-academic partners across the FAroGels network, including during the planned secondments.

Participate actively in FAroGels network meetings, training schools, workshops and transferable-skills activities.

Prepare scientific reports, contributions to project deliverables, presentations and publications, and contribute to dissemination and communication activities.

Supervisory team and planned secondments

The Doctoral Candidate will be supervised by a team combining academic and non-academic expertise:

Said Adil Atlioglu, Superex (Pard Mühendislik ve Otomasyon Sanayi Ticaret Ltd. Şti.), Türkiye (main supervisor, non-academic); Dr. Halit Çavuşoğlu, Selçuk University (SU), Türkiye (main supervisor at the PhD awarding institution); Prof. Dr. Mecit Halil Öztop, Middle East Technical University (METU), Türkiye (academic co-supervisor); and Dr. Irina Smirnova, Technische Universitat Hamburg (TUHH), Germany (academic co-supervisor).

As part of the training programme, the Doctoral Candidate will complete planned secondments at FAroGels partner organisations:

University of Santiago de Compostela (USC), academic, Spain, 3 months; The Nottingham Trent University (TNTU), academic, United Kingdom, 2 months; Technische Universitat Hamburg (TUHH), academic, Germany, 1 month; and aerogel-it GmbH (AIt), non-academic, Germany, 1 month.