-
independently without direct supervision 8. Proven experience in analysing high-throughput genomic data, particularly WGS and GWAS datasets. Desirable criteria 1. UpToDate knowledge of machine learning
-
. UpToDate knowledge of machine learning methods applied to clinical or omics data 2. Research experience in Neuroscience 3. Experience in grant writing 4. Experience in supervising staff and
-
. Experienced in developing machine learning and generative AI solutions for deployment into production. Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch, Keras) Strong programming skills in
-
for. You should apply if We are seeking an enthusiastic and dedicated researcher with a strong track record in data analyses and a passion for machine learning and artificial intelligence in healthcare. You
-
, data analytics, artificial intelligence, machine learning, etc. will be advantageous. Work independently, as well as within a team, to ensure that the project can meet the milestones adhering
-
teaching, learning, and mentoring. Attachment 5: Transcript (only for applicants who have not yet received a PhD or who received a PhD within the past three years). Applicants will be sent an email with
-
software engineers as well with the ILANCE laboratory (located in Japan) in order to build a strong leadership in Machine-Learning based algorithms. Frequent travels to Japan and CERN (working at ILANCE
-
, and optimization; automation, machine learning, and VR/AR applications in construction; construction safety; and innovative project delivery. The individual will complement and align with the skills and
-
production Use of new and future digital tools in the field of materials research (AI/machine learning, digital twinning of material development and manufacturing processes) "High-throughput processing
-
++, Python, LabView) and firmware development. Working experience with IoT, data analytics, artificial intelligence, machine learning, etc. Extensive hands-on experience and knowledge of industry practices